Post-Doctoral Research Associate for Hydrological Model and Analysis Platform, University of Maryland
Duties:
The University of Maryland/Earth System Science Interdisciplinary Center (UMD/ESSIC)
has an opening for a Post-doctoral Associate in the framework of multiple
NASA-funded projects. The successful candidate will be working full time
at the Hydrological Sciences Laboratory at NASA Goddard Space Flight Center (GSFC)
in Greenbelt, MD. In these projects, we focus on:
(1) the development of land surface models and the global scale Hydrological Model
and Analysis Platform (HyMAP) river routing scheme, including the implementation
of anthropogenic activities and evaluation of impacts on the water and energy cycles;
(2) multivariate data assimilation, including GRACE-based terrestrial water storage,
soil moisture and radar altimetry data;
(3) extreme hydrological event (droughts and floods) forecasts; and
(4) applied sciences and capacity building with partners in West Africa.
More Info
✔️ @ApplyTime
Duties:
The University of Maryland/Earth System Science Interdisciplinary Center (UMD/ESSIC)
has an opening for a Post-doctoral Associate in the framework of multiple
NASA-funded projects. The successful candidate will be working full time
at the Hydrological Sciences Laboratory at NASA Goddard Space Flight Center (GSFC)
in Greenbelt, MD. In these projects, we focus on:
(1) the development of land surface models and the global scale Hydrological Model
and Analysis Platform (HyMAP) river routing scheme, including the implementation
of anthropogenic activities and evaluation of impacts on the water and energy cycles;
(2) multivariate data assimilation, including GRACE-based terrestrial water storage,
soil moisture and radar altimetry data;
(3) extreme hydrological event (droughts and floods) forecasts; and
(4) applied sciences and capacity building with partners in West Africa.
More Info
✔️ @ApplyTime
@ApplyTime.pdf
15.9 KB
Research and Teaching Assistant, PhD in Communication Sciences, Università della Svizzera italiana, Lugano, Switzerland
✔️ @ApplyTime
✔️ @ApplyTime
PhD positions in Advanced Machine Learning at Cambridge (deadline 5th of December), University of Cambridge
The Machine Learning Group at the University of Cambridge is looking for exceptional students for its PhD programme in Advanced Machine Learning.
The Cambridge Machine Learning Group (http://mlg.eng.cam.ac.uk) is internationally renowned, comprising about 30 researchers, including Prof. Zoubin Ghahramani, Prof. Carl Edward Rasmussen, Dr. Rich Turner, Dr. Jose Miguel Hernandez Lobato and Dr. Adrian Weller.
We encourage applications from outstanding candidates with a keen interest in doing basic research in machine learning and its scientific applications. There are no additional restrictions on the topic of the PhD but for further information on our current research areas please consult our webpages at http://mlg.eng.cam.ac.uk
Applicants should hold (or be expected to hold) a degree in Information Engineering, Electrical Engineering, Statistics, Physics, or Computer Science preferably with 1st class honours (or equivalent). Some practical experience of machine learning or statistics would be strongly preferred (e.g. coursework assignments or research).
Application deadline: 5th of December, 2018.
Details about the application process can be found here:
http://mlg.eng.cam.ac.uk/?page_id=659
Applicants must formally apply through the Applicant Portal at the University of Cambridge
https://www.graduate.study.cam.ac.uk/applicant-portal
by 12:00pm (midday) UK time on the day of the deadline, indicating “PhD in Engineering” as the course (supervisor Hernandez-Lobato, Rasmussen, Turner, and/or Weller). Applicants that want to apply for University funding need to reply ‘Yes’ to the question ‘Apply for Cambridge Scholarships’. See http://www.admin.cam.ac.uk/students/gradadmissions/prospec/apply/deadlines.html for details. Note that applications will not be complete until all the required material has been uploaded (including reference letters) and we will not be able to see any application until that happens.
✔️ @ApplyTime
The Machine Learning Group at the University of Cambridge is looking for exceptional students for its PhD programme in Advanced Machine Learning.
The Cambridge Machine Learning Group (http://mlg.eng.cam.ac.uk) is internationally renowned, comprising about 30 researchers, including Prof. Zoubin Ghahramani, Prof. Carl Edward Rasmussen, Dr. Rich Turner, Dr. Jose Miguel Hernandez Lobato and Dr. Adrian Weller.
We encourage applications from outstanding candidates with a keen interest in doing basic research in machine learning and its scientific applications. There are no additional restrictions on the topic of the PhD but for further information on our current research areas please consult our webpages at http://mlg.eng.cam.ac.uk
Applicants should hold (or be expected to hold) a degree in Information Engineering, Electrical Engineering, Statistics, Physics, or Computer Science preferably with 1st class honours (or equivalent). Some practical experience of machine learning or statistics would be strongly preferred (e.g. coursework assignments or research).
Application deadline: 5th of December, 2018.
Details about the application process can be found here:
http://mlg.eng.cam.ac.uk/?page_id=659
Applicants must formally apply through the Applicant Portal at the University of Cambridge
https://www.graduate.study.cam.ac.uk/applicant-portal
by 12:00pm (midday) UK time on the day of the deadline, indicating “PhD in Engineering” as the course (supervisor Hernandez-Lobato, Rasmussen, Turner, and/or Weller). Applicants that want to apply for University funding need to reply ‘Yes’ to the question ‘Apply for Cambridge Scholarships’. See http://www.admin.cam.ac.uk/students/gradadmissions/prospec/apply/deadlines.html for details. Note that applications will not be complete until all the required material has been uploaded (including reference letters) and we will not be able to see any application until that happens.
✔️ @ApplyTime
Cambridge Machine Learning Group
Cambridge Machine Learning Group.
OPEN RESEARCH POSITION in DEEP LEARNING FOR COMPUTER VISION
An opening is available for a RESEARCH POSITION at the University of
Ljubljana in the area of deep learning for computer vision. The opening
is available within a national research project funded by the Slovenian
Research Agency (ARRS). The goal of the project is to develop deep
learning models able to infer volumetric part-based models from visual
data, e.g., depth images, point clouds, intensity images, etc. The
appointment is from January 1st, 2019 (may be delayed a few (1-3) months
if needed) until June 30th, 2020 with a possible extension.
If the candidate does not hold a PhD degree, enrollment into the
Doctoral School of the University of Ljubljana is also possible.
Project web-site: http://lrv.fri.uni-lj.si/sqnn/
Work description
The candidate is expected to:
• Conduct research in the scope of a fundamental ARRS project
• Develop deep learning solutions for the recovery volumetric models
from visual data
• Publish results in peer reviewed vision-oriented journals and
conferences
• Collaborate with students and research staff on related projects
Expected qualifications
• MSc or PhD degree in computer science or related fields
• Outstanding programming skills, e.g., Python, Matlab, C++
• Experience with deep learning frameworks, e.g., Keras, PyTorch, Caffe
• Familiarity with computer vision tools and libraries, e.g., OpenCV,
VLFeat
• Good track record – publications in SCI indexed journals and
top-tier conferences
• Excellent oral and written communication skills (in English)
How to apply
Interested candidates should send a CV with a detailed description of
skills and research experience and a cover letter with the e-mail
subject [ARRS SQ: Research application] to Assoc. Prof. Peter Peer
(peter.peer@fri.uni-lj.si) and Assoc. Prof. Vitomir Struc
(vitomir.struc@fe.uni-lj.si). Review of applications will start on
December 10th and will continue until the position is filled. Feel free
to contact us if you have any questions.
✔️ @ApplyTime
An opening is available for a RESEARCH POSITION at the University of
Ljubljana in the area of deep learning for computer vision. The opening
is available within a national research project funded by the Slovenian
Research Agency (ARRS). The goal of the project is to develop deep
learning models able to infer volumetric part-based models from visual
data, e.g., depth images, point clouds, intensity images, etc. The
appointment is from January 1st, 2019 (may be delayed a few (1-3) months
if needed) until June 30th, 2020 with a possible extension.
If the candidate does not hold a PhD degree, enrollment into the
Doctoral School of the University of Ljubljana is also possible.
Project web-site: http://lrv.fri.uni-lj.si/sqnn/
Work description
The candidate is expected to:
• Conduct research in the scope of a fundamental ARRS project
• Develop deep learning solutions for the recovery volumetric models
from visual data
• Publish results in peer reviewed vision-oriented journals and
conferences
• Collaborate with students and research staff on related projects
Expected qualifications
• MSc or PhD degree in computer science or related fields
• Outstanding programming skills, e.g., Python, Matlab, C++
• Experience with deep learning frameworks, e.g., Keras, PyTorch, Caffe
• Familiarity with computer vision tools and libraries, e.g., OpenCV,
VLFeat
• Good track record – publications in SCI indexed journals and
top-tier conferences
• Excellent oral and written communication skills (in English)
How to apply
Interested candidates should send a CV with a detailed description of
skills and research experience and a cover letter with the e-mail
subject [ARRS SQ: Research application] to Assoc. Prof. Peter Peer
(peter.peer@fri.uni-lj.si) and Assoc. Prof. Vitomir Struc
(vitomir.struc@fe.uni-lj.si). Review of applications will start on
December 10th and will continue until the position is filled. Feel free
to contact us if you have any questions.
✔️ @ApplyTime
Postdoc position on measurement theory in machine learning, jointly at Bristol and the Alan Turing Institute
I am offering a two-year postdoctoral position starting early 2019 to work on the important topic of measurement theory and its uses in machine learning, data science and AI. PhD positions may also available. Please get in touch if the below sounds of interest.
Issues of measurement are of particular importance in inductive sciences including data science and artificial intelligence, for example when we asses the capability of our models and learning algorithms to generalise beyond the observed data.
This project funded by the Alan Turing Institute will seek to make fundamental advances in our understanding of capabilities and skills of models and algorithms in data science and AI , and how to measure those capabilities and skills. Just as psychometrics has developed tools to model the skills of a human learner and develop standardised (SAT) tests, so we need similar tools to model the skills of learning machines and have standardised benchmarks which will allow skill assessment with only a few well-chosen test sets.
This is a great opportunity to work on a timely and important topic and spend time at the Turing Institute. To be considered for this position you need a solid background in machine learning, excellent mathematical skills and an interest in foundational research.
Peter Flach, Turing Fellow, University of Bristol
http://people.cs.bris.ac.uk/~flach
http://www.turing.ac.uk/people/researchers/peter-flach
✔️ @ApplyTime
I am offering a two-year postdoctoral position starting early 2019 to work on the important topic of measurement theory and its uses in machine learning, data science and AI. PhD positions may also available. Please get in touch if the below sounds of interest.
Issues of measurement are of particular importance in inductive sciences including data science and artificial intelligence, for example when we asses the capability of our models and learning algorithms to generalise beyond the observed data.
This project funded by the Alan Turing Institute will seek to make fundamental advances in our understanding of capabilities and skills of models and algorithms in data science and AI , and how to measure those capabilities and skills. Just as psychometrics has developed tools to model the skills of a human learner and develop standardised (SAT) tests, so we need similar tools to model the skills of learning machines and have standardised benchmarks which will allow skill assessment with only a few well-chosen test sets.
This is a great opportunity to work on a timely and important topic and spend time at the Turing Institute. To be considered for this position you need a solid background in machine learning, excellent mathematical skills and an interest in foundational research.
Peter Flach, Turing Fellow, University of Bristol
http://people.cs.bris.ac.uk/~flach
http://www.turing.ac.uk/people/researchers/peter-flach
✔️ @ApplyTime
The Alan Turing Institute
Peter Flach
Peter Flach is Professor of Artificial Intelligence at the University of Bristol. His main research is in the area of mining highly structured data and the evaluation and improvement of machine learning models using ROC analysis. He has also published on…
Neuroscience, Baylor College of Medicine
Position ID: BCM-POSTDOC [#13285]
Position Title: Postdoctoral Research Fellow
Position Type: Postdoctoral
Position Location: Houston, Texas 77030, United States [map]
Application Deadline: 2019/11/29 (posted 2018/11/29, listed until 2019/11/29)
Position Description:
POSITION: We seek several highly motivated postdoctoral research fellows for a collaborative team project building statistical tools for interpreting large scale neural recordings. The fellows will develop new methods and applications of probabilistic graphical models to infer statistical interactions amongst neurons and with their environment. The tools will be validated in neural network simulations, tested in physiological recordings, and made widely available to the neuroscience community for understanding data from next-generation experiments.
TEAM: Fellows will join principal investigators and theorists Krešimir Josić, Genevera Allen, Xaq Pitkow, Ankit Patel, and Robert Rosenbaum. The team will interact closely with experimentalists including co-Investigator Andreas Tolias and several other labs interested in applying novel methods we develop. Fellows will also be members of the new Center for Neuroscience and Artificial Intelligence housed at the Baylor College of Medicine and supported in part by the NSF NeuroNex program. The Center brings together interdisciplinary researchers from across Houston, including members from Baylor College of Medicine, Rice University, University of Houston, and University of Texas Health Sciences. Researchers at the Center contribute diverse expertise in fields including neuroscience, machine learning, statistics, physics, computer science, electrical engineering, and applied mathematics.
QUALIFICATIONS: Candidates must have outstanding mathematical skills, a PhD in a relevant quantitative discipline, and expertise in probabilistic graphical models or statistical machine learning.
APPLYING: Applicants should email a letter of research interests and CV to Camila Lopez (Camila.Lopez@bcm.edu), along with contact information for three references. We look forward to hearing from you!
✔️ @ApplyTime
Position ID: BCM-POSTDOC [#13285]
Position Title: Postdoctoral Research Fellow
Position Type: Postdoctoral
Position Location: Houston, Texas 77030, United States [map]
Application Deadline: 2019/11/29 (posted 2018/11/29, listed until 2019/11/29)
Position Description:
POSITION: We seek several highly motivated postdoctoral research fellows for a collaborative team project building statistical tools for interpreting large scale neural recordings. The fellows will develop new methods and applications of probabilistic graphical models to infer statistical interactions amongst neurons and with their environment. The tools will be validated in neural network simulations, tested in physiological recordings, and made widely available to the neuroscience community for understanding data from next-generation experiments.
TEAM: Fellows will join principal investigators and theorists Krešimir Josić, Genevera Allen, Xaq Pitkow, Ankit Patel, and Robert Rosenbaum. The team will interact closely with experimentalists including co-Investigator Andreas Tolias and several other labs interested in applying novel methods we develop. Fellows will also be members of the new Center for Neuroscience and Artificial Intelligence housed at the Baylor College of Medicine and supported in part by the NSF NeuroNex program. The Center brings together interdisciplinary researchers from across Houston, including members from Baylor College of Medicine, Rice University, University of Houston, and University of Texas Health Sciences. Researchers at the Center contribute diverse expertise in fields including neuroscience, machine learning, statistics, physics, computer science, electrical engineering, and applied mathematics.
QUALIFICATIONS: Candidates must have outstanding mathematical skills, a PhD in a relevant quantitative discipline, and expertise in probabilistic graphical models or statistical machine learning.
APPLYING: Applicants should email a letter of research interests and CV to Camila Lopez (Camila.Lopez@bcm.edu), along with contact information for three references. We look forward to hearing from you!
✔️ @ApplyTime
PhD positions in Nanoscience of Biology, Chemistry, Physics, Material Science, and related
100% positions for 4 years,
earliest starting date: 1. January 2019
The Swiss Nanoscience Institute (SNI) at the University of Basel invites highly motivated scientists to apply for the SNI PhD program in Nanoscience. The eight successful PhD candidates will join an attractive interdisciplinary programme together with the ~30 currently supported scientists. The available positions cover a wide variety of topics, including cutting edge quantum physics and chemistry, material science, nanotechnology, biochemistry and cell biology.
Your position
The following projects are available:
Bioinspired nanoscale drug delivery systems for efficient targeting and safe in vivo application
From Schrödinger's equation to biology: Unsupervised quantum machine learning for directed evolution of anti-adhesive peptides
Nanoscale mechanical energy dissipation in quantum systems and 2D-materials
Picoscopic mass analysis of mammalian cells progressing through the cell cycle
High-throughput multiplexed microuidics for antimicrobial drug discovery
Image the twist!
Andreev Spin Qubit (ASQ) in GeSi Nanowires
Quantum dynamics of an ultracold ion coupled to a nanomechanical oscillator
More information on the individual projects can be found at phd.nanoscience.ch
Your profile
We are looking for very motivated researchers with a Master's degree in Natural Sciences, ideally in a topic relevant for the respective project. All projects require the abilities to work independently, interact with other researchers, presentation skills, and a solid basis in scientific research.
We offer you
Excellent scientific and social environment
Very competitive employment conditions
Membership in a very supportive and recognised community
Application / Contact
More information and the online application form can be found at phd.nanoscience.ch. For questions please contact the head of the SNI PhD programme, Dr. Andreas Baumgartner (andreas.baumgartner@unibas.ch), or directly the respective project leaders. The complete application has to be submitted before 31 December 2018. Please note that the decision to fill a given vacancy can be taken at any time from now.
www.unibas.ch
Apply Now
✔️ @ApplyTime
100% positions for 4 years,
earliest starting date: 1. January 2019
The Swiss Nanoscience Institute (SNI) at the University of Basel invites highly motivated scientists to apply for the SNI PhD program in Nanoscience. The eight successful PhD candidates will join an attractive interdisciplinary programme together with the ~30 currently supported scientists. The available positions cover a wide variety of topics, including cutting edge quantum physics and chemistry, material science, nanotechnology, biochemistry and cell biology.
Your position
The following projects are available:
Bioinspired nanoscale drug delivery systems for efficient targeting and safe in vivo application
From Schrödinger's equation to biology: Unsupervised quantum machine learning for directed evolution of anti-adhesive peptides
Nanoscale mechanical energy dissipation in quantum systems and 2D-materials
Picoscopic mass analysis of mammalian cells progressing through the cell cycle
High-throughput multiplexed microuidics for antimicrobial drug discovery
Image the twist!
Andreev Spin Qubit (ASQ) in GeSi Nanowires
Quantum dynamics of an ultracold ion coupled to a nanomechanical oscillator
More information on the individual projects can be found at phd.nanoscience.ch
Your profile
We are looking for very motivated researchers with a Master's degree in Natural Sciences, ideally in a topic relevant for the respective project. All projects require the abilities to work independently, interact with other researchers, presentation skills, and a solid basis in scientific research.
We offer you
Excellent scientific and social environment
Very competitive employment conditions
Membership in a very supportive and recognised community
Application / Contact
More information and the online application form can be found at phd.nanoscience.ch. For questions please contact the head of the SNI PhD programme, Dr. Andreas Baumgartner (andreas.baumgartner@unibas.ch), or directly the respective project leaders. The complete application has to be submitted before 31 December 2018. Please note that the decision to fill a given vacancy can be taken at any time from now.
www.unibas.ch
Apply Now
✔️ @ApplyTime
Please see the attached PDF for three postdoc openings at Duke University under Prof. Vahid Tarokh (http://people.duke.edu/~vt45/):
1. Postdoctoral Fellowship in Physics Inspired Approaches to Artificial Intelligence
2. Postdoctoral Fellowship in Data-Driven Approaches to Stochastic Adversarial Games
3. Postdoctoral Fellowship in Non-Commutative Information Theory and Processing
To apply, please follow the instructions in the attached PDF.
For inquiries, please contact Prof. Tarokh directly.
http://people.duke.edu/~vt45/postdocads.pdf
✔️ @ApplyTime
1. Postdoctoral Fellowship in Physics Inspired Approaches to Artificial Intelligence
2. Postdoctoral Fellowship in Data-Driven Approaches to Stochastic Adversarial Games
3. Postdoctoral Fellowship in Non-Commutative Information Theory and Processing
To apply, please follow the instructions in the attached PDF.
For inquiries, please contact Prof. Tarokh directly.
http://people.duke.edu/~vt45/postdocads.pdf
✔️ @ApplyTime
Post-doc fellowship in modeling effects of urban stormwater regulations on channel erosion
The Department of Biological Systems Engineering at Virginia Tech is seeking a Postdoctoral Fellow to assist in a Chesapeake Bay Trust-funded research project. The project will evaluate the impacts of traditional and “low impact development” (LID) stormwater control measures (SCMs) on channel erosion. Two streams in the Baltimore-Washington DC area will be modeled using an urban watershed model (SWMM) and a channel evolution model (CONCEPTS), which will be coupled using an existing external control program, RSWMM. The two watersheds represent extremes in development patterns, i.e., nearly no control to extensive implementation of LID controls. Both watersheds have detailed data records sufficient to develop and test coupled models. Study results will compare the impact of traditional and LID practices on channel stability for each watershed and provide insight into the causes and potential solutions to channel degradation resulting from urbanization.
The selected individual will work with Drs. Theresa Thompson and David Sample of Virginia Tech, and Dr. Andrew Miller of University of Maryland, Baltimore County. The selected individual will lead model development and programming efforts, and will also participate in field data collection.
Please visit www.jobs.vt.edu, posting SR0180212 to apply for this position.
Required Qualifications
PhD in agricultural, biological, or biological systems engineering, civil/environmental engineering, hydrology, or related field completed by January 1, 2019.
Experience with hydrologic modeling and geographic information systems (GIS).
Knowledge of hydrology, hydraulics, water quality, and sediment transport.
Strong computer programming abilities, preferably R, Python, and/or Matlab.
Strong verbal and written English communication skills.
Preferred Qualifications
Experience with the SWMM and CONCEPTS.
Field experience with best management practices (BMPs), water quality and/or stream/river assessments. The ability to independently traverse rough, densely vegetated terrain will be needed.
Experience with model sensitivity, uncertainty analyses, and optimization.
Drivers license in any state and the ability to obtain a drivers license in Virginia within 30 days of appointment. Driving record will be assessed prior to hire.
The BSE Department at Virginia Tech is recognized both nationally and internationally for its education, research, and extension and outreach programs. The BSE Department consists of 17 tenured and tenure-track faculty, eight research scientists/research associates, three extension specialists/associates, and 12 technical staff/administrative professionals. Additional information about the BSE Department can be found at https://www.bse.vt.edu.
Virginia Tech is a public land-grant university, committed to teaching and learning, research, and outreach to the Commonwealth of Virginia, the nation, and the world. Building on its motto of Ut Prosim (that I may serve), Virginia Tech is dedicated to InclusiveVT—serving in the spirit of community, diversity, and excellence. We seek candidates who adopt and practice the Principles of Community, which are fundamental to our on-going efforts to increase access and inclusion, and to create a community that nurtures learning and growth for all of its members. Virginia Tech actively seeks a broad spectrum of candidates to join our community in preparing leaders for the world.
✔️ @ApplyTime
The Department of Biological Systems Engineering at Virginia Tech is seeking a Postdoctoral Fellow to assist in a Chesapeake Bay Trust-funded research project. The project will evaluate the impacts of traditional and “low impact development” (LID) stormwater control measures (SCMs) on channel erosion. Two streams in the Baltimore-Washington DC area will be modeled using an urban watershed model (SWMM) and a channel evolution model (CONCEPTS), which will be coupled using an existing external control program, RSWMM. The two watersheds represent extremes in development patterns, i.e., nearly no control to extensive implementation of LID controls. Both watersheds have detailed data records sufficient to develop and test coupled models. Study results will compare the impact of traditional and LID practices on channel stability for each watershed and provide insight into the causes and potential solutions to channel degradation resulting from urbanization.
The selected individual will work with Drs. Theresa Thompson and David Sample of Virginia Tech, and Dr. Andrew Miller of University of Maryland, Baltimore County. The selected individual will lead model development and programming efforts, and will also participate in field data collection.
Please visit www.jobs.vt.edu, posting SR0180212 to apply for this position.
Required Qualifications
PhD in agricultural, biological, or biological systems engineering, civil/environmental engineering, hydrology, or related field completed by January 1, 2019.
Experience with hydrologic modeling and geographic information systems (GIS).
Knowledge of hydrology, hydraulics, water quality, and sediment transport.
Strong computer programming abilities, preferably R, Python, and/or Matlab.
Strong verbal and written English communication skills.
Preferred Qualifications
Experience with the SWMM and CONCEPTS.
Field experience with best management practices (BMPs), water quality and/or stream/river assessments. The ability to independently traverse rough, densely vegetated terrain will be needed.
Experience with model sensitivity, uncertainty analyses, and optimization.
Drivers license in any state and the ability to obtain a drivers license in Virginia within 30 days of appointment. Driving record will be assessed prior to hire.
The BSE Department at Virginia Tech is recognized both nationally and internationally for its education, research, and extension and outreach programs. The BSE Department consists of 17 tenured and tenure-track faculty, eight research scientists/research associates, three extension specialists/associates, and 12 technical staff/administrative professionals. Additional information about the BSE Department can be found at https://www.bse.vt.edu.
Virginia Tech is a public land-grant university, committed to teaching and learning, research, and outreach to the Commonwealth of Virginia, the nation, and the world. Building on its motto of Ut Prosim (that I may serve), Virginia Tech is dedicated to InclusiveVT—serving in the spirit of community, diversity, and excellence. We seek candidates who adopt and practice the Principles of Community, which are fundamental to our on-going efforts to increase access and inclusion, and to create a community that nurtures learning and growth for all of its members. Virginia Tech actively seeks a broad spectrum of candidates to join our community in preparing leaders for the world.
✔️ @ApplyTime
Two-Year MSc level Research Associate (Artificially intelligent digital learning platform)
An exciting opportunity has become available for a master level candidate to build an Artificially Intelligent digital Learning platform for English language training; with adaptive virtual teaching agents and embedded gamification environments to support stimulated student interaction. This position is a 24 month fixed term contract, with a GBP 4k dedicated training budget tailored towards your personal development.
More Info
✔️ @ApplyTime
An exciting opportunity has become available for a master level candidate to build an Artificially Intelligent digital Learning platform for English language training; with adaptive virtual teaching agents and embedded gamification environments to support stimulated student interaction. This position is a 24 month fixed term contract, with a GBP 4k dedicated training budget tailored towards your personal development.
More Info
✔️ @ApplyTime
Three research associate positions in machine learning / deep learning: generative models; curiosity-driven learning; program synthesis
Three research associate positions in machine learning / deep learning are offered for about 2 years (until December 2020), at the Romanian Institute of Science and Technology (RIST) in Cluj, Romania. Applications will be assessed on a rolling basis and the starting date may be as soon as the selected candidates are available.
The positions correspond to one or more of the following topics:
1. Studying generative models, autoencoders or compressors for data with long-range or hierarchical structure, in particular: a) web pages (HTML / CSS code), and b) sensorimotor data – vectors of perceptions and actions recorded over extended timeframes.
2. Studying curiosity-driven learning, deep reinforcement learning, hierarchical reinforcement learning and meta-learning for: a) tasks typically used as benchmarks in the field, such simulators or games; or b) artificial intelligent agents that interact directly with a computer, for example generating HTML / CSS code, or more general software.
3. Studying new approaches to program synthesis that may integrate machine learning / deep learning, reinforcement learning, evolutionary methods, and classical approaches.
4. Applied research on machine learning systems that are trained on large repositories of web pages and learn to generate HTML / CSS or similar code. This should lead to systems that automatically upgrade websites or to systems that learn to generate web pages with a state-of-the-art design conditioned on mockups drawn by clients.
We are looking for self-motivated, independent, creative scientists, with strong analytical and computational modeling skills. A PhD is preferred but we also accept candidates with a Master degree and research experience proven by scientific publications or relevant completed projects. Candidates could have a background in machine learning, physics, computer science, robotics, engineering, computational neuroscience or related fields. We welcome candidates with no prior experience in machine learning but with a strong publication record. Programming skills are required.
Net salary is 1,800-2,300 euros per month for PhDs and 1,300-1,800 euros per month for persons with no PhD, while the cost of living in Cluj is significantly lower than in Western Europe or the USA.
Cluj, the main city of Transylvania, hosts Romania’s largest university and boasts a strong, rapidly developing IT industry.
More information is available at: https://rist.ro/research-associate-positions-machine-learning-deep-learning/
Interested candidates may meet the group leader, Răzvan Valentin Florian, at NeurIPS until December 9.
✔️ @ApplyTime
Three research associate positions in machine learning / deep learning are offered for about 2 years (until December 2020), at the Romanian Institute of Science and Technology (RIST) in Cluj, Romania. Applications will be assessed on a rolling basis and the starting date may be as soon as the selected candidates are available.
The positions correspond to one or more of the following topics:
1. Studying generative models, autoencoders or compressors for data with long-range or hierarchical structure, in particular: a) web pages (HTML / CSS code), and b) sensorimotor data – vectors of perceptions and actions recorded over extended timeframes.
2. Studying curiosity-driven learning, deep reinforcement learning, hierarchical reinforcement learning and meta-learning for: a) tasks typically used as benchmarks in the field, such simulators or games; or b) artificial intelligent agents that interact directly with a computer, for example generating HTML / CSS code, or more general software.
3. Studying new approaches to program synthesis that may integrate machine learning / deep learning, reinforcement learning, evolutionary methods, and classical approaches.
4. Applied research on machine learning systems that are trained on large repositories of web pages and learn to generate HTML / CSS or similar code. This should lead to systems that automatically upgrade websites or to systems that learn to generate web pages with a state-of-the-art design conditioned on mockups drawn by clients.
We are looking for self-motivated, independent, creative scientists, with strong analytical and computational modeling skills. A PhD is preferred but we also accept candidates with a Master degree and research experience proven by scientific publications or relevant completed projects. Candidates could have a background in machine learning, physics, computer science, robotics, engineering, computational neuroscience or related fields. We welcome candidates with no prior experience in machine learning but with a strong publication record. Programming skills are required.
Net salary is 1,800-2,300 euros per month for PhDs and 1,300-1,800 euros per month for persons with no PhD, while the cost of living in Cluj is significantly lower than in Western Europe or the USA.
Cluj, the main city of Transylvania, hosts Romania’s largest university and boasts a strong, rapidly developing IT industry.
More information is available at: https://rist.ro/research-associate-positions-machine-learning-deep-learning/
Interested candidates may meet the group leader, Răzvan Valentin Florian, at NeurIPS until December 9.
✔️ @ApplyTime
Romanian Institute of Science and Technology
Three research associate positions in machine learning / deep learning: generative models; curiosity-driven learning, deep reinforcement…
Three research associate positions are available within a EU-funded project. The postdoctoral research associates will work on generative models; curiosity-driven learning…
PhD Scholarship in Department of Geology, at University of Ghent
Job description
The Renard Centre of Marine Geology (Department of Geology) is offering a PhD position (4y) in the framework of the FWO research project DynaMOD “an oceanographic and sediment DYNamic MODelling study of MOunded contourite Drifts”.
The PhD scholarship is fully funded for four years and preferably starts in April 2019. The DynaMOD project will focus on the increase of bottom current intensity in the presence of a seabed with a complex topography such as cold-water coral mounds. Previous investigations along the upper eastern slope (300-800 m depth) of the Porcupine Seabight (off Ireland) have indicated a sufficiently small area having the potential to become a unique natural laboratory to investigate this present and past sediment dynamic variability. Firstly, it is aimed to understand and quantify the temporal and spatial variability of the present-day hydrodynamic regime. Secondly, through an acoustic dissection of the subseafloor, we aim to obtain a pseudo-3D view of the contourite drift, formed due to the action of bottom currents. This will enable the reconstruction of the architectural evolution during the past 2 million years, supported by correlation to nearby IODP boreholes. Based upon these present and past observations, 3D numerical modelling will simulate the past palaeohydrodynamic variability to better understand the oceanographic drivers behind the contourite drift construction. For this purpose, the PhD student will apply an integrated approach which is built upon a large legacy dataset using seismic profiling, as well as very-high resolution observations using oceanographic moorings and AUV and ROV technologies.
More Info
✔️ @ApplyTime
Job description
The Renard Centre of Marine Geology (Department of Geology) is offering a PhD position (4y) in the framework of the FWO research project DynaMOD “an oceanographic and sediment DYNamic MODelling study of MOunded contourite Drifts”.
The PhD scholarship is fully funded for four years and preferably starts in April 2019. The DynaMOD project will focus on the increase of bottom current intensity in the presence of a seabed with a complex topography such as cold-water coral mounds. Previous investigations along the upper eastern slope (300-800 m depth) of the Porcupine Seabight (off Ireland) have indicated a sufficiently small area having the potential to become a unique natural laboratory to investigate this present and past sediment dynamic variability. Firstly, it is aimed to understand and quantify the temporal and spatial variability of the present-day hydrodynamic regime. Secondly, through an acoustic dissection of the subseafloor, we aim to obtain a pseudo-3D view of the contourite drift, formed due to the action of bottom currents. This will enable the reconstruction of the architectural evolution during the past 2 million years, supported by correlation to nearby IODP boreholes. Based upon these present and past observations, 3D numerical modelling will simulate the past palaeohydrodynamic variability to better understand the oceanographic drivers behind the contourite drift construction. For this purpose, the PhD student will apply an integrated approach which is built upon a large legacy dataset using seismic profiling, as well as very-high resolution observations using oceanographic moorings and AUV and ROV technologies.
More Info
✔️ @ApplyTime
www.ugent.be
PhD student — Ghent University
oap-en - 100% - 2019/02/01 16:00:00 GMT+1 - WE13
PhD Scholarship Position in electrochemistry, at Technical University of Munich
TOPIC
Proton exchange membrane fuel cells (PEMFCs) are a very promising energy conversion device, especially for transportation applications. However, their mass market penetration requires a significant cost reduction and further improvements in performance and durability. In this PhD-project, you will work with a team of researchers from 10 different industrial and research institutions from 4 countries on the development of PEM fuel cell membrane electrode assemblies (MEAs) for automotive applications by optimizing the catalyst and its implementation in cathode catalyst layers.
More Info
✔️ @ApplyTime
TOPIC
Proton exchange membrane fuel cells (PEMFCs) are a very promising energy conversion device, especially for transportation applications. However, their mass market penetration requires a significant cost reduction and further improvements in performance and durability. In this PhD-project, you will work with a team of researchers from 10 different industrial and research institutions from 4 countries on the development of PEM fuel cell membrane electrode assemblies (MEAs) for automotive applications by optimizing the catalyst and its implementation in cathode catalyst layers.
More Info
✔️ @ApplyTime
Esrc Wales Dtp PhD Studentship in Management and Business
Cardiff Business School, supported by the ESRC Doctoral Training Partnership for Wales (Wales DTP), invites applications for PhD study, with the possibility of being awarded a fully-funded ESRC DTP Studentship, available to start in October 2019.
We expect to make doctoral studentship awards in the area of management and business.
Research is at the centre of Cardiff Business School's activities. Cardiff Business School is ranked 6th in the UK for the quality of its research in the 2014 Research Excellence Framework (REF) and is one of only two business schools in the UK to be ranked in the top ten in each of the Government’s five assessment exercises since 1992.
Research is conducted both within the School's sub-disciplinary groups as well as via specialist and multidisciplinary research centres. Cardiff Business School has an international faculty of world-leading scholars and its research reputation has helped it become an attractive centre of scholarship for colleagues from the UK and beyond.
More Info
✔️ @ApplyTime
Cardiff Business School, supported by the ESRC Doctoral Training Partnership for Wales (Wales DTP), invites applications for PhD study, with the possibility of being awarded a fully-funded ESRC DTP Studentship, available to start in October 2019.
We expect to make doctoral studentship awards in the area of management and business.
Research is at the centre of Cardiff Business School's activities. Cardiff Business School is ranked 6th in the UK for the quality of its research in the 2014 Research Excellence Framework (REF) and is one of only two business schools in the UK to be ranked in the top ten in each of the Government’s five assessment exercises since 1992.
Research is conducted both within the School's sub-disciplinary groups as well as via specialist and multidisciplinary research centres. Cardiff Business School has an international faculty of world-leading scholars and its research reputation has helped it become an attractive centre of scholarship for colleagues from the UK and beyond.
More Info
✔️ @ApplyTime
PhD student in Biomedicine, Lund University
Work duties
This project aims at defining the mechanisms involved in the development of neurodegeneration and neuroinflammation in obesity-related diabetes, leading to brain dysfunction. In addition to identifying the involved molecular pathways, morphological and functional changes will be monitored non-invasively with magnetic resonance imaging and behaviour experiments.
Qualifications
Requirements
Master degree in Biomedicine or similar subject.
Good knowledge of neurophysiology.
Previous research experience in Diabetes and Neuroscience.
Experience with brain tissue preparations, molecular biology methods, immunohistochemistry and microscopy, and protein immunoblotting.
Fluency in English.
Merits
FELASA certification for animal research or equivalent.
Experience on investigating neurodegeneration and neuroinflammation.
Understanding of neuroimaging methods.
More Info
✔️ @ApplyTime
Work duties
This project aims at defining the mechanisms involved in the development of neurodegeneration and neuroinflammation in obesity-related diabetes, leading to brain dysfunction. In addition to identifying the involved molecular pathways, morphological and functional changes will be monitored non-invasively with magnetic resonance imaging and behaviour experiments.
Qualifications
Requirements
Master degree in Biomedicine or similar subject.
Good knowledge of neurophysiology.
Previous research experience in Diabetes and Neuroscience.
Experience with brain tissue preparations, molecular biology methods, immunohistochemistry and microscopy, and protein immunoblotting.
Fluency in English.
Merits
FELASA certification for animal research or equivalent.
Experience on investigating neurodegeneration and neuroinflammation.
Understanding of neuroimaging methods.
More Info
✔️ @ApplyTime
Ph.D. opportunity in tropical ecohydrology: field AND computational
A motivated, prepared Ph.D. student is sought for highly interdisciplinary research in a project funded by the National Science Foundation focusing on ecohydrology and ecophysiology of rainforest function.
— Must have field experience and be able to work in the field: 2-4 week long campaigns in hot & humid Amazon rainforest;
— Must be fluent with programming languages and willing to expand computational proficiency in HPC;
— M.S./M.S.E. degree in Physics or Engineering or Geosciences; minor in Biology is a plus;
— Fluency in Portuguese is a plus (willingness to learn is a must);
— The thesis will address the diversity of ecohydrologic traits and their impact on forest drought resilience;
— PhD Program: Department of Civil & Environmental Eng., University of Michigan, Ann Arbor, USA
Please send a short statement of motivation, a copy of transcripts, and a CV to ivanov@umich.edu
—Valeriy Ivanov
----------------------------------------
Associate Professor
Department of Civil & Environmental Eng., University of Michigan
1351 Beal Avenue, 105 EWRE, Ann Arbor, MI 48109-2125
Phone: (734) 763-5068; Fax: (734) 763-2275
http://www.umich.edu/~ivanov
✔️ @ApplyTime
A motivated, prepared Ph.D. student is sought for highly interdisciplinary research in a project funded by the National Science Foundation focusing on ecohydrology and ecophysiology of rainforest function.
— Must have field experience and be able to work in the field: 2-4 week long campaigns in hot & humid Amazon rainforest;
— Must be fluent with programming languages and willing to expand computational proficiency in HPC;
— M.S./M.S.E. degree in Physics or Engineering or Geosciences; minor in Biology is a plus;
— Fluency in Portuguese is a plus (willingness to learn is a must);
— The thesis will address the diversity of ecohydrologic traits and their impact on forest drought resilience;
— PhD Program: Department of Civil & Environmental Eng., University of Michigan, Ann Arbor, USA
Please send a short statement of motivation, a copy of transcripts, and a CV to ivanov@umich.edu
—Valeriy Ivanov
----------------------------------------
Associate Professor
Department of Civil & Environmental Eng., University of Michigan
1351 Beal Avenue, 105 EWRE, Ann Arbor, MI 48109-2125
Phone: (734) 763-5068; Fax: (734) 763-2275
http://www.umich.edu/~ivanov
✔️ @ApplyTime
Entry-level research assistant position in clinical neuroimaging at Stony Brook University
Dear colleagues,
If you have former students looking for full-time employment coordinating and running fMRI, PET and other clinical procedures in psychiatric patient populations (especially schizophrenia and substance abuse), I would encourage you to invite them to apply for a newly opened position in my lab in the Psychiatry Department at Stony Brook. We are a multidisciplinary, multi-PI lab with backgrounds in Psychiatry, Psychology, Mathematics, Radiology, and Biomedical Engineering. Applicants should apply via the link below prior to Dec 18. Please note that applicants should pay extra attention to the “preferred qualifications” listed on the posting, and ensure that all qualifications that they meet are clearly indicated on their resume or cover letter.
https://stonybrooku.taleo.net/careersection/2/jobdetail.ftl?job=1803781&tz=GMT-05%3A00
Please share this posting as widely as possible.
Thank you for your time,
-Jared
--
Jared Van Snellenberg, PhD
Assistant Professor
Department of Psychiatry & Behavioral Health
Departments of Psychology and Biomedical Engineering
Renaissance School of Medicine at Stony Brook University
www.mmtilab.org
www.jaredvs.com
Phone: (631) 638-0064
HSC Level 10 Room 087J
101 Nicolls Road
Stony Brook, NY 11794-8101
_______________________________
"If we knew what it was we were doing, it would not be called research, would it?"
-Albert Einstein
✔️ @ApplyTime
Dear colleagues,
If you have former students looking for full-time employment coordinating and running fMRI, PET and other clinical procedures in psychiatric patient populations (especially schizophrenia and substance abuse), I would encourage you to invite them to apply for a newly opened position in my lab in the Psychiatry Department at Stony Brook. We are a multidisciplinary, multi-PI lab with backgrounds in Psychiatry, Psychology, Mathematics, Radiology, and Biomedical Engineering. Applicants should apply via the link below prior to Dec 18. Please note that applicants should pay extra attention to the “preferred qualifications” listed on the posting, and ensure that all qualifications that they meet are clearly indicated on their resume or cover letter.
https://stonybrooku.taleo.net/careersection/2/jobdetail.ftl?job=1803781&tz=GMT-05%3A00
Please share this posting as widely as possible.
Thank you for your time,
-Jared
--
Jared Van Snellenberg, PhD
Assistant Professor
Department of Psychiatry & Behavioral Health
Departments of Psychology and Biomedical Engineering
Renaissance School of Medicine at Stony Brook University
www.mmtilab.org
www.jaredvs.com
Phone: (631) 638-0064
HSC Level 10 Room 087J
101 Nicolls Road
Stony Brook, NY 11794-8101
_______________________________
"If we knew what it was we were doing, it would not be called research, would it?"
-Albert Einstein
✔️ @ApplyTime
Postdoctoral Scholar Programme on Socio-Economic Inequality
The Stone Center on Socio-Economic Inequality at The Graduate Center announced a new postdoctoral program that will support two scholars beginning in the 2019-2020 academic year and two beginning in the 2020-2021 year.
The program will enable postdoctoral scholars, or postdocs, to spend two years producing empirical research on topics such as earnings, income, and wealth inequality. One position is reserved for a scholar whose research focuses on high-end wealth. For a second position, the Stone Center will give priority to applicants whose work investigates aspects of wealth at any point of the wealth/income distribution. The remaining positions will be awarded to scholars researching other areas of inequality.
The Stone Center is the home of the U.S. office of LIS (formerly the Luxembourg Income Study Center), the renowned cross-national income and wealth data archive. The postdocs will join a team with deep experience using the data, and will work closely with the center’s six core faculty members: professor Gornick, Leslie McCall, Paul Krugman, Branko Milanovic, Salvatore Morelli, and Miles Corak.
Each postdoc will receive an annual salary, benefits including health insurance, funding to hire Graduate Center students as research assistants, and additional support to help offset the costs of hardware and software, books and journals, and travel. The new program is funded by a philanthropic gift of $1.2 million from The James M. and Cathleen D. Stone Foundation.
A key feature of the program is the option for a clinical placement in the second year. Placements will be available in applied policy settings such as congressional offices, nonprofit research institutions, and policy think tanks.
Postdocs will divide their time between their own research projects, collaborations with senior scholars associated with the center, and contributions to public learning through lectures, writing, and other outreach to diverse audiences and scholars in the field.
To apply to the postdoctoral position focused on high-end wealth, see here. To apply to the position focused on other areas of socio-economic inequality, see here.
Applications for fall 2019 are due by January 15.
More Info
✔️ @ApplyTime
The Stone Center on Socio-Economic Inequality at The Graduate Center announced a new postdoctoral program that will support two scholars beginning in the 2019-2020 academic year and two beginning in the 2020-2021 year.
The program will enable postdoctoral scholars, or postdocs, to spend two years producing empirical research on topics such as earnings, income, and wealth inequality. One position is reserved for a scholar whose research focuses on high-end wealth. For a second position, the Stone Center will give priority to applicants whose work investigates aspects of wealth at any point of the wealth/income distribution. The remaining positions will be awarded to scholars researching other areas of inequality.
The Stone Center is the home of the U.S. office of LIS (formerly the Luxembourg Income Study Center), the renowned cross-national income and wealth data archive. The postdocs will join a team with deep experience using the data, and will work closely with the center’s six core faculty members: professor Gornick, Leslie McCall, Paul Krugman, Branko Milanovic, Salvatore Morelli, and Miles Corak.
Each postdoc will receive an annual salary, benefits including health insurance, funding to hire Graduate Center students as research assistants, and additional support to help offset the costs of hardware and software, books and journals, and travel. The new program is funded by a philanthropic gift of $1.2 million from The James M. and Cathleen D. Stone Foundation.
A key feature of the program is the option for a clinical placement in the second year. Placements will be available in applied policy settings such as congressional offices, nonprofit research institutions, and policy think tanks.
Postdocs will divide their time between their own research projects, collaborations with senior scholars associated with the center, and contributions to public learning through lectures, writing, and other outreach to diverse audiences and scholars in the field.
To apply to the postdoctoral position focused on high-end wealth, see here. To apply to the position focused on other areas of socio-economic inequality, see here.
Applications for fall 2019 are due by January 15.
More Info
✔️ @ApplyTime
3-year postdoc position: using fMRI to study the interaction of attention and motivation
We are currently accepting applications for a postdoctoral position in the lab of Bianca Wittmann at the University of Giessen, Germany, just 70 km north of Frankfurt.
The project will investigate the interaction of attentional processes and reward learning using fMRI. Our department offers a research-dedicated 3T MRI scanner with eye-tracking and peripheral physiology equipment. The project is part of the Collaborative Research Centre SFB/TRR 135 under the umbrella theme “Cardinal mechanisms of perception: Prediction, valuation, categorization” (www.sfb-perception.de). The Collaborative Research Centre offers a creative, cooperative environment uniting leading experts in vision research.
The successful candidate will be responsible for collecting and analyzing fMRI data using computational models of learning and decision-making, writing scientific papers and teaching in biological psychology according to the teaching regulations of the state of Hesse. We offer funding for research visits in collaborating research groups abroad (e.g. Princeton University, PI: Yael Niv).
We are looking for highly motivated candidates with a PhD in neuroscience, psychology, biology or a related field. Candidates should have good programming skills and prior publications using fMRI and/or computational modeling of learning or decision making.
For further information, please contact bianca.wittmann@psychol.uni-giessen.de.
✔️ @ApplyTime
We are currently accepting applications for a postdoctoral position in the lab of Bianca Wittmann at the University of Giessen, Germany, just 70 km north of Frankfurt.
The project will investigate the interaction of attentional processes and reward learning using fMRI. Our department offers a research-dedicated 3T MRI scanner with eye-tracking and peripheral physiology equipment. The project is part of the Collaborative Research Centre SFB/TRR 135 under the umbrella theme “Cardinal mechanisms of perception: Prediction, valuation, categorization” (www.sfb-perception.de). The Collaborative Research Centre offers a creative, cooperative environment uniting leading experts in vision research.
The successful candidate will be responsible for collecting and analyzing fMRI data using computational models of learning and decision-making, writing scientific papers and teaching in biological psychology according to the teaching regulations of the state of Hesse. We offer funding for research visits in collaborating research groups abroad (e.g. Princeton University, PI: Yael Niv).
We are looking for highly motivated candidates with a PhD in neuroscience, psychology, biology or a related field. Candidates should have good programming skills and prior publications using fMRI and/or computational modeling of learning or decision making.
For further information, please contact bianca.wittmann@psychol.uni-giessen.de.
✔️ @ApplyTime
Two PhD Scholarship Wideband Optical Network Nodes and Techniques
Work environment
Eindhoven University of Technology (https://www.tue.nl/en/) is one of Europe’s top technological universities, situated at the heart of a most innovative high-tech region. Thanks to a wealth of collaborations with industry and academic institutes, our research has real-world impact. TU/e is ranked among the first 100 in the Times Higher Educational World University ranking and 49th in the Shanghai ARWU ranking (engineering). TU/e has around 3,000 employees and 2,300 PhD students (half of which international, representing about 70 nationalities).
The candidate will work at the Department of Electrical Engineering (https://www.tue.nl/en/university/departments/electrical-engineering/). Within this department, research and education is done in domains of Telecommunication, Care and Cure, and Smart energy systems. The interfaculty Institute for Photonic Integration (IPI) performs research in the area of broadband telecommunication, by investigating the potential of optical technologies. As a key member of IPI, the Electro-Optical Communication Systems (ECO) group focuses its research on optical communication system techniques, ranging from systems for ultra-high capacity long reach transmission (encompassing single-mode, multi-mode and multi-core fiber systems), ultra-fast (all-) optical packet switching nodes, high-density intra-data center networks, to multi-service flexible access and in-building networks (including radio-over-fibre and optical wireless communication). ECO participates in several national and international projects.
More Info
✔️ @ApplyTime
Work environment
Eindhoven University of Technology (https://www.tue.nl/en/) is one of Europe’s top technological universities, situated at the heart of a most innovative high-tech region. Thanks to a wealth of collaborations with industry and academic institutes, our research has real-world impact. TU/e is ranked among the first 100 in the Times Higher Educational World University ranking and 49th in the Shanghai ARWU ranking (engineering). TU/e has around 3,000 employees and 2,300 PhD students (half of which international, representing about 70 nationalities).
The candidate will work at the Department of Electrical Engineering (https://www.tue.nl/en/university/departments/electrical-engineering/). Within this department, research and education is done in domains of Telecommunication, Care and Cure, and Smart energy systems. The interfaculty Institute for Photonic Integration (IPI) performs research in the area of broadband telecommunication, by investigating the potential of optical technologies. As a key member of IPI, the Electro-Optical Communication Systems (ECO) group focuses its research on optical communication system techniques, ranging from systems for ultra-high capacity long reach transmission (encompassing single-mode, multi-mode and multi-core fiber systems), ultra-fast (all-) optical packet switching nodes, high-density intra-data center networks, to multi-service flexible access and in-building networks (including radio-over-fibre and optical wireless communication). ECO participates in several national and international projects.
More Info
✔️ @ApplyTime