Post doc position starting in April 2021
- The postdoctoral researcher will be offered the opportunity to evolve in a dynamic international environment, within the context of the IW-NET project funded under H2020-EU3.4, gathering 26 industrial and academic partners from 9 different European countries (www.iw-net.eu).
- We are looking for a motivated postdoctoral researcher whose responsibilities would primarily include the design and development of optimization-based decision support systems dedicated to tactical and operational planning of intermodal barge freight transportation.
- The contribution of the research work is proposing and evaluating advanced optimization and decision-making methodologies for vehicle and service planning, demand booking, predictive routing, and execution of transportation activities, enabling synchromodality on IWT networks.
- Optimization and decision-making methodologies based on RM concepts and techniques will be deployed on practical application scenarios in collaboration with European project partners.
- The objective is to assess the capability of RM based DSS to settle up favorable conditions for an innovative structural service offer and for a new equilibrium concerning operations and interactions between IWT stakeholders.
Strong skills in English scientific writing are a pre-requisite; knowledge of French, or willingness to learn, would make life in Valenciennes (FR) more enjoyable.
The position is open to candidates of any nationality and selection will be based on the candidate’s research record and potential.
To apply
This is a two-year position, available immediately. Applications will be received until the position is filled.
The application should be submitted by e-mail to ioana.bilegan@uphf.fr, and should include, in a single PDF file, the following elements:
Dr. Ioana BILEGAN
Maître de conférences [Associate Professor]
Université Polytechnique Hauts-de-France (UPHF)
Scholarship Programme for the Masters in Global Health and Clinical Research: International Health Track
The grants are offered to students from sub-Saharan Africa and will cover the total of the tuition and the registration fees
Students from sub-Saharan Africa can now apply to the ISGlobal scholarship programme to pursue the Master in Global Health and, for the first time, the Master in Clinical Research: International Health Track, for the 2020-2021 period. These scholarships cover the total of the tuition fees and the university taxes required for a complete registration programme.
Between 2017 and 2019, ISGlobal has granted four scholarships, which have been highly appreciated by the grantees. For Daniel Kwakye, “this scholarship represents ISGlobal’s commitment to ensuring an equal say in Global Health for people from all cultures and backgrounds”. Ifeyinwa Martins, another grantee, says “the scholarship has not only transformed me as a student but also as an individual thanks to the sharing of experiences with wonderful people from all over the world”.
The deadline for submitting the application and the required documentation ends on April 5, 2020. Thereafter, the suitability of the applications will be evaluated and selected according to the process described in the documents listed below.
Candidates must meet a series of requirements, such as having the nationality of a sub-Saharan African country and residing there; holding a Bachelor’s university degree, and demonstrating a high level of written and spoken English. They must also show a strong commitment with global health values —health equity, care for vulnerable populations and acceptance of diversity—, passion to improve the health status of their communities, and a clear understanding of the international challenges the health community faces.
More information:
https://www.isglobal.org/en/-/isglobal-renueva-su-programa-de-becas-para-los-masteres-en-salud-global-e-investigacion-clinica-salud-internacional
PhD Position Joint Doctoral Program NITech Japan
The Joint Degree Doctoral Program in Informatics is a joint doctoral degree program between Nagoya Institute of Technology (NITech) Japan, and University of Wollongong (UOW) Australia. Students who graduate from the program are awarded a joint doctoral degree from both institutions. The program is designed to turn out researchers who are able to create super smart societies, contribute to the fourth industrial revolution, and lead the world in pioneering new areas of study within the field of Artificial Intelligence. Our aim is to develop practical researchers and engineers who will serve as global leaders, paving the way for new innovations at multinational companies, and developing a worldwide impact. Nagoya Institute of Technology is offering a number of fully funded PhD positions for students from around the globe to join this program. We are looking for students with experience and Interest, who have good theoretical and mathematical foundations and who want to help lead the way towards the next generation of intelligent systems that have the ability to think and learn from humans. The successful candidate is expected to conduct research in abroad range of topics in Artificial Intelligence including, but no limited to, the following:
● Artificial Intelligence (with emphasis on multiagent systems)
● Machine Learning (with emphasis on deep reinforcement learning)
● Big Data Management and Analysis
● Collective Intelligence (with emphasis on smart city applications)
● Internet of Things and Industry 4.0
Requirements
● Master degree from a reputed university.
● IELTS academic module overall score of 6.5 with no band score less than 6.0.
(TOEFL is also accepted).
● Good mathematical skills.
● Good programming skills.
Benefits
● A custom-tailored curriculum to prepare you for a career in artificial intelligence
and machine learning research for universities and companies.
● A creative, diverse, and collaborative working environment in one of the world’s
most innovative and most livable areas.
● Integration into the NITech AI research center, which offers regular opportunities
(courses, workshops, international study trips) for learning more about AI,
Machine Learning and closely related topics and linking up with interdisciplinary
teams.
● Opportunities for participating in international research conferences and for
connecting with scientists and practitioners around the world.
● Additional funding for equipment and travel.
● Competitive compensation.
● English-speaking work environment.
Application Process
In order to apply, please email the following documents to (ahmed@nitech.ac.jp).
● Cover Letter
● Resume
● Certificates and transcripts (BSc and MSc)
● IELTS/TOEFL score
Please email your documents with the title “JDP Application”
Start Date
The candidate should be able to start the PhD studies as soon as possible. We will review the applications on a rolling basis, please submit your application as soon as possible. In addition, the successful candidate may need to sit an admission interview according to the university regulations.
Contact
Dr. Ahmed Moustafa, Email ahmed@nitech.ac.jp
PhD Positions in Discrete Optimization and Data Analysis at King’s College London
Two PhD positions are available:
Postdoctoral position : Affective image and video content analysis for entertainment and education
Postdoctoral position : Affective image and video content analysis for entertainment and education- University of Poitiers (XLIM)
The University of Poitiers and the XLIM laboratory has an opening for recent PhD or Postdoc with expertise in multimedia data analysis and machine learning with a focus on deep learning and multimodal data processing.
The postdoctoral researcher will work on affective analysis of multimedia data for entertainment and education. This fellowship is a part of the CPER-FEDER project “E-Education” in partnership with the European Union. The fellowship has a duration of 12 months with possibility of extension. The candidate will work on developing new deep learning-based approaches for image and video affective content understating, classification, and retrieval. He/she will have access to local datasets and computational resources, including GPUs. The postdoctoral researcher will work in collaboration with researchers on cognitive and educational psychology from the CERCA-CNRS laboratory.
We are seeking highly qualified and motivated candidate with a PhD in Computer Vision, Machine Learning, Image processing or a closely related field, a relevant scientific track record on major computer vision conferences/journals is a criterion for the selection as well as experience on deep learning techniques and platforms. Experience on affective computing is considered a plus for this position.
Application:
Please include a CV, a statement of research interests and 2 letters of reference emailed to Olfa Ben Ahmed at olfa.ben.ahmed@univ-poitiers.fr. The call will remain open until the position is filled but a first deadline for evaluation of candidates will be 26 February 2021. The post-doc contract will start during April 2021.
Best regards — Dr. Olfa BEN AHMED Associate professor/Maître de conférences XLIM – University of PoitiersMember of ICONES team Bât SP2MI, 11 Bd Marie et PierreCurie, 86962 Chasseneuil Cedex,France phone : +33 (0)5 49 49 74 91 fax : +33 (0)5 49 49 65 70 email : olfa.ben-ahmed@xlim.fr
Post-doc machine learning and geolocalization of non geotagged-tweets
An 18-month post-doctoral position will be opened on machine learning and geolocalization of non geotagged-tweets, in France’s reference public institution for Earth Science applications (BRGM) and National Mapping Agency (IGN).
Background and motivations:
SURICATE-Nat (www.suricatenat.fr) is a collaborative platform for the semi-automatic analysis of tweets written in French related to natural disasters (for instance, earthquakes or floods). This platform aims to exploit the testimonies immediately after a natural disaster in order to promote a rapid rise of information by «citizen sensors». This involves extracting the main information from the tweets: type of disaster, damage, location etc. Location is a particularly important piece of information as it helps the relief agencies to deal with the disaster effectively, but state of the art approaches for tweet geolocalization often fail to provide accurate location.
Missions :
The main mission of the post-doctorate fellow would therefore be to propose new approaches to improve the accuracy and the precision of the automatic geolocalization of tweets, which is a necessary step to accurately describe the effects of natural disasters.
He/she will contribute to the scientific state of the art in several fields:
– recognition, extraction and contextualization of geographic information that can be found in tweets messages,
– spatial named entities resolution and text geocoding.
The successful candidate will work in direct collaboration with researchers from both BRGM and IGN research teams, as well as researchers from the ANR funded project « RéSoCIO», having an established expertise in geographic information extraction, spatial named entity resolution, knowledge management and machine learning.
More details are available in attachment or directly on this Web page : https://brgm-recrute.talent-soft.com/offre-de-emploi/emploi-post-doctoral-position-inferring-a-precise-geolocalization-from-tweets-about-natural-disas-h-f_1704.aspx
Application :
If you have any questions about the position, please contact us.
To apply, send us your application (updated CV and cover letter) until March 19, 2021, through the BRGM recruitment website or by email:
– Samuel Auclair (s.auclair@brgm.fr)
– Cécile Gracianne (c.gracianne@brgm.fr)
– Guillaume Touya (guillaume.touya@ign.fr)
– Nathalie Abadie (nathalie-f.abadie@ign.fr)
Post-doc and Intern Positions in Machine Learning for Medicine
Dear Friends and Colleagues,
I am looking for Post-docs and research interns to join my team at MIT for a project on machine learning for sequential treatment decision making in medicine. Please help forward the following posting to potential candidates. Thanks.
I am looking for highly-motivated Post-docs and Research Interns to join my team at MIT for a project on machine learning for sequential treatment decision making and outcome prediction. The project offers opportunities to develop advanced machine learning methods to derive insights from heterogeneous, longitudinal observational data from electronic health records (including physiological/clinical time series and signals, images, medications/procedures, and text-based medical reports) for informed treatment decision making.
The ideal candidate will have demonstrated an outstanding capability for independent research and a solid publication record in top-tier machine learning, AI conferences, or other top-tier ML for healthcare conferences and journals. Post-doc candidate must hold an advanced degree in Computer Science, Machine Learning, Statistics, or a related field.
Immediate openings are available for the following positions. Postdoc Associate is a one-year funded position with a possibility for renewal depending on funding availability. Postdoc Fellow is for candidates who have secured independent funding covering all expenses (e.g., through external Fellowship programs). Ph.D. candidates who are enrolled in one of the top Computer Science programs may apply for Visiting Student or Summer Intern positions. Applicants should submit a curriculum vitae and links to three most relevant publications to Li Lehman (lilehman<at>mit.edu) ASAP.
Fully funded PhD position: Applying argumentation theory in legal reasoning
PhD contract: 3 years, starting October 2021
Srdjan Vesic (CNRS – CRIL UMR 8188 – Université d’Artois)
Nathalie Nevejans (CDEP – Université d’Artois)
Junior group leader position (bioinformatics, computational biology, theoretical biological physics) – Institut Curie, Paris
Applications from outstanding candidates wishing to address questions on the
fundamental mechanisms of nuclear organization, genome biology and epigenetics, through
computational and/or modeling approaches are welcome.
We are looking for candidates with a strong
expertise in bioinformatics, computational biology and/or theoretical biological physics as well
as a proven ability to collaborate with experimentalists. If needed, occasional access to wet lab
space can be provided.
See the attached flyer for more informations.
Call2020_JPI_Position_UMR3664_INSTITUT CURIE
Sincerely,
Phd offer: Integration of Machine Learning into the Resolution of MO-VRPTWs with Applications in Hospital Environment
** Apologies for cross-posting **
** Please forward to anybody who might be interested. **
ORKAD (Operations Research, Knowledge And Data) is a research team within the OPTIMA thematic group of the CRIStAL research center (Centre de Recherche en Informatique, Signal et Automatique de Lille) (UMR CNRS 9189) of the University of Lille (France). The main objective of the ORKAD team is to simultaneously exploit combinatorial optimization and data mining in order to solve optimization problems. Despite the two scientific domains having evolved more or less independently from each other, the synergy between combinatorial optimization and data mining offers the opportunity of improving the performance of optimization methods with help data mining and, on the other hand, to solve data mining problems more efficiently with the help of operations research methods [Dhaenens-Jourdan2016]. Our approaches are mainly based on mono- and multi-objective combinatorial optimization.
INOCS (INtegrated Optimization problems with Complex Structure) is an INRIA’s research team part of the OPTIMA group of CRIStAL in Lille(France). The INOCS team aims to develop new models, algorithmic techniques and implementations for problems with complex structure according to three types of optimization paradigms: mathematical optimization, bilevel optimization and robust/stochastic optimization.
This thesis is a collaboration between the two teams, ORKAD and INOCS. The objective of the thesis is to investigate the use of machine learning techniques to solve multi-objective combinatorial optimization problems and in particular Multi-Objective Vehicle Routing Problems with Time Windows.
This thesis aims to investigate the use of machine learning to solve Multi-Objective Combinatorial Optimization Problems and in particular the MO-VRPTW [Jozefowiez2008]. A number of studies have emerged in recent years to integrate learning techniques in optimization algorithms for routing problems. These works have shown that discovering the structural properties of high-quality solutions, can strongly affect and enhance the performance of heuristic algorithms for routing problems [Arnold2019c]. It is also well known that high-quality solutions of a vehicle routing problem are highly similar to optimal solutions, that is, are structurally close to the global optima. Generally, a single objective that usually models an economical aspect is taken into account in the modelisation of the problem. This may be acceptable when merchandise is transported, but may not be the case when it comes to the transport of people. In the latter case, it is essential to take into account the comfort of the passengers, while assuring to obtain low cost routes to enhance the performance of the service company.
This leads to a compromise where both aspects are taken into account, i.e., multi-objective optimization.
First, the transposition to the multi-objective case of the method developed in [Arnold2019a] will be studied and experiments will be conducted on literature benchmarks. Then, the aim will be to investigate and understand how the properties of high-quality solutions with respect to optimal solutions adapt to the multi-objective context, where, usually, the optimization of one objective results in the detriment of the other(s). This will lead to the development of novel ways to integrate machine learning in both exact algorithms and metaheuristics.
IMU-Simons African Fellowship Program
Are you an African employed in Africa who wants to travel to an internationally known mathematical centre of excellence for collaborative research? Apply for the IMU-Simons African Fellowship Program for a grant to cover your travel and living expenses. More details here:
https://www.mathunion.org/cdc/grants/research-travel-grants/imu-simons-african-fellowship-program
PhD position Designing AI systems able of minimizing user anxiety in Umeå University
MIT-huset, Umeå university
Deadline: 31st of March 2021
https://www.umu.se/en/work-with-us/open-positions/phd-student-position-in-designing-artificial-intelligence-systems-_372470/
Classic AI systems generally focus on raw performance metrics, such as minimizing the time or cost to reach a goal. By doing so, these systems tend to create an unnecessary constant exposure to anxiety, as optimizing for performance involves “cutting edges as short as possible”.
Think of a GPS or tool such as google maps for finding the shortest itinerary: the fastest route generally offers no slack: if a bus gets delayed then following connections are likely missed–disregarding whether there is a plane to be caught in the end. What if the system would propose another route, say 10% longer, but with a very high certainty of no delay? How much user anxiety would such alternatives avoid?
In this research, the PhD student will contribute to the study of how to design AI systems capable of assessing the anxiety situations can cause to various actors and how to adjust decisions in a way that balances system performance and the anxiety experienced by the users. This trend virtually applies for any existing AI-powered system that relates to human users (e.g. city planning, itineraries, robotics) and for assessing strategies developed by humans (e.g. accounting for immediate and long-term anxiety in crisis-reaction plans).
This research involves the following general tasks: 1) understand the dynamics of anxiety from a human-science perspective (psychology, cognitive science, behavioural science, philosophy); 2) build computational models of anxiety and include such models within goal-oriented systems; 3) develop software based on these models; 4) apply these models for validation in user experiments.
Within Umeå University and under the umbrella of the WASP-HS program of excellence, the PhD student will develop a high interdisciplinary profile and expertise on making computational human cognitive models; including these models in state-of-the-art AI problem-solving; and become an expert in AI systems responsible design.
The successful applicant will be employed by Umeå University and receive salary for a period equivalent of four years of full time PhD studies.
Deadline for application: 31st of March 2021; expected starting date 1st of June 2021
Application link:
https://www.umu.se/en/work-with-us/open-positions/phd-student-position-in-designing-artificial-intelligence-systems-_372470/
Open doctoral position – Helmholtz School for Marine Data Science
Dear All,
position at Alfred Wegener Institute (Bremerhaven, Germany) within the
Helmholtz School for Marine Data Science (MarDATA).A detailed description (including a link to apply) can be found here:https://www.awi.de/en/work-study/jobs/job-offer.html
(Job no.: 21/43/G/MarData-b)The successful candidate will be co-supervised by myself and work on the
following topics:- Statistical analysis of multivariate ecological time series
– Application of (time-varying) copula models to investigate spatial
dependencies
– Implementation and real data analysis
More information about MarDATA can be found here: https://www.mardata.de/
Phd position in industrial manufacturing
We are pleased to announce open PhD positions in the PRIME (Predictive Rendering In Manufacture and Engineering) project.
PRIME brings some of the main European actors in the field of rendering research together. In addition to a high profile academic consortium (7 universities involved), the network can offer students a number of prominent end users of accurate rendering technology as industrial partners. Having the likes of IKEA, Procter & Gamble, Weta Digital, Zeiss and Adobe all together in one project offers unique opportunities to see multiple real world usage cases for predictive rendering technology in action.
These eight institutions will in total hire 15 Early Stage Researchers (ESRs) for the duration of their three year participation in the project, and will be in charge of their training plans. Seven of the eight beneficiaries are world-class universities and academic institutions, who will enrol the hired ESRs in their Ph.D. programmes. The eight beneficiary, Luxion, is a company in Denmark, where the Ph.D. training will be overseen by the nearby Danish Technical University, which is also one of the seven academic beneficiaries.
Motivated and creative candidates should hold a Master´s degree in either Computer Science, Mathematics, or Physics and have a solid background in computer graphics. Excellent programming skills and fluent English are essential. You may apply even if you are already a Ph.D. candidates elsewhere – we can establish a collaboration with your current advisor. Start date is as soon as possible.
The goal of this project is to develop skills and protocols needed for industrial usage of Predictive Rendering (PR) technologies – image synthesis which delivers results that one can actually rely on to be visually accurate. Application areas of such systems are in such diverse areas as product design, architecture, sensor system calibration, training of autonomous vehicle systems, movie VFX and manufacturing control. Goal of the ITN is to collectively train young researchers in this promising, future-oriented and research-driven application area. Each PhD student has an industrially relevant cutting-edge research topic.
Please refer to PRIME website and apply for the position accordingly:
http://prime-itn.eu/positions.html
15 PhD projects
Please find below a link to 15 PhD projects that are currently being advertised as part of the new Horizon 2020 Marie Skłodowska-Curie Actions, Innovative Training Network (ITN) called CriticalEarth that Peter Ditlevsen will be leading from UCPH in collaboration with a strong network of beneficiaries and partners. Please feel free to share to any qualified candidates in the fields of climate dynamics, climate theory, applied mathematics, statistical mechanics etc.
Click here for positions: https://www.criticalearth.eu/climate/
Some of the PhD adverts are open for applications and the remaining positions will be posted online within the next month. You can see status of each PhD via the link, including the title, location and brief overview of objectives.
CriticalEarth will officially begin on March 1st and will have a close relationship with TiPES. The 3-year PhD Fellowships will start between March and the end of September 2021 and successful applicants will form a network of 15 PhD Fellows (or “early stage researchers”, as referred to by the EU), trained to research new methods for assessing the mechanisms and associated risks of critical transitions in the climate. The focus will be on investigating how complex mathematics can be used to predict and avoid irreversible climate change. The positions will offer candidates an excellent background, working within a strong, cross-disciplinary network among leading universities and research institutions across Europe and with contacts to industry, governmental- and non-governmental institutions.
Eligibility
*Applicants should hold an MSc degree in a relevant field with great results and good English skills.
*Because the aim of EU ITN projects is to attract candidates from worldwide locations, applicants must not have resided and not have carried out their main activity (work, studies, etc.) in the country of the recruiting beneficiary for more than 12 months in the 3 years immediately before the recruitment date – unless as part of a procedure for obtaining refugee status under the Geneva Convention. If candidates are applying from a location that requires a visa or permit, then the university/institute responsible for the PhD will provide support and advice throughout the process of relocation.
*The applicant must be an Early Stage Researcher (ESR) i.e. at the time of recruitment they must be in the first 4 years (full-time equivalent research experience) of their research careers and must not have been awarded a doctoral degree.
Please let me know if you have any questions.
Kind regards
Eliza
Dr Eliza Cook
Assist. Prof.
Physics of Ice, Climate and Earth (PICE)
Niels Bohr Institute
Københavns Universitet
Copenhagen, Denmark
PhD Studentship at Strathclyde, Glasgow in fluid mechanics
Please see the attached poster, and see the information here: https://www.findaphd.com/phds/project/electrohydrodynamics-of-droplet-pairs/?p129412.
Interested students are also encouraged to email Debashish Das at debasish.das@strath.ac.uk for further information.
Proposition: PhDFile.pdf
Two Postdoc Position Opportunities at CMU-Africa
Carnegie Mellon University Africa (CMU-Africa, https://www.africa.engineering.cmu.edu/) invites applications for a fully funded postdoctoral research associate position around the design, implementation, and deployment of digital identity management systems in resource/infrastructure limited environment.
Digital financial services (DFS) constitute a key strategic pillar to advance financial inclusion in developing regions. Financial inclusion leverages innovative digital technologies involving new players, new business models, and new distribution channels servicing a set of new consumers typically using low-cost devices with limited security features. However, given the digital nature of financial service delivery in low capacity countries, cyber risk is rapidly growing and dynamically evolving. A large hack of a financial inclusion related system erodes trust in DFS from both regulators as well as consumers. Hence, protecting DFS in underserved areas should be a priority in the digitalization process of economies.
More can be found here…
Carnegie Mellon University Africa (CMU-Africa, https://www.africa.engineering.cmu.edu/) invites applications for a fully funded postdoctoral research associate position in Security and Resilience of Self-Organized Networks at its location in Kigali, Rwanda.
This international research effort aims at developing models and algorithms for security, resilience, and agility of next generation communication networks (e.g., 5G, SDN). These networks are expected to have a high degree of self-organization and will be composed of several sub-systems, each being a self-organized system by itself. The complex interactions of these multiple decision-making systems lead to emergent behaviors that are unintended and unanticipated. However, given the vital role they play in our modern society, these networks must be secure and able to withstand and rapidly recover from all hazards.
Successful candidate is expected to develop high-quality research and forge productive collaborations. The postdoc is expected to leverage recent developments in cybersecurity models, game theory, and machine learning to develop tools and algorithms that will lead to the design, implementation, and operation of self-organized networks with the necessary resilience and performance guarantees.
More can be found here…
Post-doctoral position M/W in LAAS-CNRS
General information
Workplace : TOULOUSE
Date of publication : Tuesday, January 19, 2021
Type of Contract : FTC Scientist
Contract Period : 12 months
Expected date of employment : 1 April 2021
Proportion of work : Full time
Remuneration : The monthly gross salary can vary between 2648 and 3054€ depending on the experience
Desired level of education : PhD
Missions
Activities
The real-time management of these uncertainties is an important source of stress for production supervisors who need to be very reactive and smart to tackle them so as to avoid any crisis situation. Facing unexpected events requires to schedule and reschedule production activities so that the production plan remains constantly consistent with the new constraints. The performance indicators have to be kept always the best as possible. Activity scheduling is in general very complex as a lot of information need to be taken simultaneously into account and also because the solution space is in general very combinatorial. To help production supervisor to tackle the intrinsic complexity of production scheduling, decision support systems (DSS) have been developed.
Many approaches dealing with the design of DSS for manufacturing systems are “techno-centered”: when unexpected events occur, algorithms automatically propose production plan reconfigurations to decision-makers. They have to validate them without really having the opportunity to fit them better. This kind of approach often requires a high level of digitalization and does not really take the human factors into account: operators are assumed to behave perfectly with predictable response times. Moreover, although the decision workload is not supported anymore by the supervisors in this approach, their stress can be even higher as the new plans can be seen as new constraints to integrate without the possibility to negotiate them. Decision-makers even try to tune the input data of the algorithms so that their output will be humanly acceptable.
On the contrary, the 5s project aims to promote a human-centered approach, which better analyses the relation between stress, cognitive effort, and uncertainty during rescheduling and better integrates DSS in the decision-making processes (with decision-makers in the loop). A real case-study of a satellite payload assembler will be considered in the course of the project 5S to assess the approach.
The candidate will have to :
– participate in the choice and the design of an innovative DSS approach taking cognitive ergonomics aspects into account;
– Implement the main algorithms of a DSS prototype to be used as a proof of concept;
– develop low and hi-fidelity HMI prototypes;
– interact deeply with the cognitive ergonomics and scientist researchers and the various decision-makers of the industrial case-study.
Skills
– a Ph.D. degree in computer science or a related field,
– good knowledge in the domain of HMIs,
– good skills in combinatorial optimization or constraint programming,
– strong computer programming skills,
– good organizational and communication skills.
PhD position in Strasbourg (Sept. 2021)
A PhD position is open at University of Strasbourg (ICube lab) – France for October 2021
Title: Multiparadigm interactive collaborative learning of image time series in interaction with the medical expert
Topic: Analysing heterogeneous image time series using supervised methods requires that the classes sought are perfectly known and defined and that the expert is able to provide a sufficient learning data set both in number and quality. Unfortunately, unsupervised methods can lead to results which do not match the potential objects/classes of interest. Faced with these difficulties, we propose to develop an innovative a collaborative framework of interactive multi-paradigm collaborative learning in which different methods, supervised or not, work together to produce “better” result. The objective of the thesis is two-fold. First, it will be to answer scientific questions regarding collaborative process such as what information to share (data, hypotheses, constraints…), how to evaluate results, what are good coordination mechanism, how to combine the opinions of the different agents and how to ensure convergence. Second, it is to enable the expert to add “on the fly” information (labels, constraints, etc.) used to guide the learning process in order to produce clusters and models closer to the expert’s “intuitions”. To do this, the expert will be actively assisted by the system, which will for example offer advice or proposals for new constraints or labelling of objects
Different fields in health domain of application are envisaged to validate our proposition. They will mainly concern situations in which the types of evolution are both numerous and not very formalized as for instance, images time series.
To apply:
The positions are offered to both foreign and French students who hold a Master degree in computer science. The candidate must have good skills in data analysis and more particularly in supervised or unsupervised classification of time series. Skills in image analysis is welcome.
Good knowledge of English (French is not mandatory)
As required by the Doctoral School of the University of Strasbourg, the candidate must have obtained all his/her Master’s (and Bachelor’s) semesters or equivalent with a grade above 12/20. He/she must also be ranked among the top 20% of graduates of his/her Master promotion.
Send your CV, transcript of grades, ranking and motivation to Pierre Gançarski (gancarski@unistra.fr) and Antoine Cornuéjols (antoine.cornuejols@agroparistech.fr)
Detailed Description: https://seafile.unistra.fr/f/3c4f54836ab44eec99b5/https://seafile.unistra.fr/f/3c4f54836ab44eec99b5/https://seafile.unistra.fr/f/3c4f54836ab44eec99b5/https://seafile.unistra.fr/f/3c4f54836ab44eec99b5/https://seafile.unistra.fr/f/3c4f54836ab44eec99b5/