2-4 Excellence PhD Scholarship Positions Within Excellence Initiative Nano, Chalmers University of Technology


We are looking for the brightest minds among all Nano-interested students at Chalmers and world-wide. The winners are awarded with one PhD-postion each, which they can place at any Nano research group at Chalmers. This is the fourth of a yearly recurring call.

Most PhD student positions at Chalmers are announced by a specific research group, funded by a specific research project. With an Excellence PhD student position you have your own funding, which of course gives you far more freedom in choosing both research group and research project.

A PhD exam in Nano is the perfect start for your career, whether you aim at academic research at the highest level, advancing technology and business ideas in major companies or spinning off your own idea into a start-up company.

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PhD Scholarship in Packaging Logistics; Logistics and Supply Chain Management, Lund University

Job assignments

The PhD position belongs to the research subject ‘packaging logistics’, where logistics and supply chain management are key areas. The research topic for the PhD student originates from packaging as an effective link to logistics in supply chains, where it contributes to the delivery and distribution of products and components with minimal resources from production to consumption. The research should develop and analyse packaging strategies that lead to effective and sustainable supply chains. The research is linked to a research project in the automotive industry on the cost and environmental impacts of packaging on supply chains.

The PhD student will be part of a research project with other researchers and representatives from the automotive industry. The PhD student will also gain access to a leading network for the Swedish and European automotive industry. Because of the potential of packaging for sustainable supply chains, the issues in this research are prioritized by the Swedish and European automotive industry. This means that the PhD student has a great opportunity to develop new knowledge and affect the automotive industry to become more sustainable and competitive. The PhD position enables the PhD student the opportunity to apply and develop his or her knowledge in logistics and supply chain management.

The main duties of doctoral students are to devote themselves to their research studies which includes participating in research projects and third cycle courses. The work duties will also include teaching and other departmental duties (no more than 20%).

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Doctoral studentship position (PhD student) in Political Science associated with the research project "Governance of Collective Action: The Case of Antibiotic Policy in the European Union"


The Department of Political Science, University of Gothenburg, is one of the leading Political Science departments in the Nordic countries. The vibrant department houses several large research institutes. It houses the Varieties of Democracy (V-Dem) Institute, the Quality of Government (QoG) Institute, the Media, Opinion, and Democracy project (MOD), and the National Election Studies. The department is also a key actor in the SOM Institute. It has 130 employees, out of which more than 70 are faculty and researchers, and it hosts about 1,400 students. The department offers education on all levels; graduate and postgraduate levels as well as courses. Education is provided for in English and Swedish.

More information about the department is available on our website.

The Department of Political science is currently looking for qualified candidates for a doctoral studentship position (PhD student) in Political Science associated with a research project on “Governance of Collective Action: The Case of Antibiotic Policy in the European Union”. The project is funded by the Swedish Research Council and is directed by Professor Jon Pierre.

We hope to recruit a social scientist who is knowledgeable in quantitative and qualitative research methods. Also, basic knowledge about the EU and theories of collective action are desirable.

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3-4 PhD Studentship Positions in Political Science, University of Gothenburg

The Department of Political Science, University of Gothenburg, is one of the leading Political Science departments in the Nordic countries. The vibrant department houses several large research institutes. It houses the Varieties of Democracy (V-Dem) Institute, the Quality of Government (QoG) Institute, the Media, Opinion, and Democracy project (MOD), and the National Election Studies. The department is also a key actor in the SOM Institute. It has 130 employees, out of which more than 70 are faculty and researchers, and it hosts about 1,400 students. The department offers education on all levels; graduate and postgraduate levels as well as courses. Education is provided for in English and Swedish.

More information about the department is available on our website.

The Department of Political Science is currently looking for qualified and motivated individuals for up to four doctoral studentship positions (PhD students) in Political Science.

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Monash University is delighted to offer a postdoctoral position in nursing. Potential candidates should apply before January 14, 2019.

The Opportunity

The Faculty of Information Technology offers vibrant and creative programs across all core IT and related subject areas, and in addition has extensive research efforts organised around core competency areas as follows: Systems and Cybersecurity, Data Science, Education, Computer-Human Interaction and Creativity, and Organisational and Social Informatics.

The Digital Health theme in the Faculty of Information Technology draws on capabilities in all the above areas, and is further grounded in collaborations with a range of other faculties across Monash, including Medicine, Nursing and Health Sciences; Engineering; Business and Economics; Art, Design and Architecture (MADA); Science and Arts.

The Faculty is seeking a Research Assistant to be a part of the new range of initiatives within Digital Health at Monash. A Research Assistant is expected to contribute towards the research effort of the university and to develop their research expertise through the pursuit of defined projects relevant to the particular field of research.

To be successful, you will ideally have an honours degree in the relevant discipline or have equivalent qualifications or research experience, and demonstrated knowledge of digital health.

This role is a full-time position; however, flexible working arrangements may be negotiated.

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Behaviour of Clay for Geo-environmental and Geotechnical Applications Postgraduate Research Scholarship, University of Sydney

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A new opening postdoctoral fellowship position in artificial intelligence is available at Australian National University, Australia. Eligible candidates should submit the applications before January 06, 2019.,

Position overview

The ANU College of Engineering and Computer Science (CECS) is dedicated to contributing to The Australian National University’s reputation for excellence in research and research-led education, bringing together expertise across a range of areas to reimagine the role of engineering and computing for future generations. CECS is a diverse and vibrant community dedicated to discovery and to making knowledge matter. Our academics and students are engaged in ground-breaking, cutting-edge research, in exciting areas such as renewable energy, robotics, telecommunications, biomaterials, human-machine interaction, and artificial intelligence.

The Research School of Computer Science (RSCS) is unique in Australia. It includes a creative mix of staff and students that embrace the breadth of computer science profession. It is a diverse and vibrant community dedicated to discovery and to making knowledge matter. It contains world-class academics undertaking high-quality research, training of research students and delivering coursework teaching programs.

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Fully-funded PhD Studentship Lorentz Electron Microscopy and Analysis of Magnetic Skyrmions, University of Cambridge

Magnetic skyrmions are an extraordinary magnetic phenomena that can be thought of as topological defects in the magnetic texture of certain materials. Cambridge is a key member of the EPSRC-funded UK-wide magnetic skyrmion project (https://www.skyrmions.ac.uk/) which aims to understand at a fundamental level the structure and dynamics of skyrmions and to develop novel magnetic devices. The project student will be an integral part of the Cambridge team collaborating with four other UK institutes to investigate the fundamental physical behaviour of magnetic skyrmions.

The project will involve TEM-based Lorentz imaging of skyrmion materials and devices using the FIB to create prototype structures. Low temperature in situ microscopy will correlate structures and composition with skyrmion lattice development and understanding better the dynamics of skrymion motion and order/disorder transitions using applied magnetic fields and electrical bias. The project will also involve micromagnetic simulations, image processing and big data analysis. Skyrmionic materials will be readily available through the Programme grant consortium.

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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.

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Research and Teaching Assistant, PhD in Communication Sciences, Università della Svizzera italiana, Lugano, Switzerland

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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.


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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.

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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

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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!

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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

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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

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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.

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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.

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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.

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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.

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