Hello, We are looking for an AI/ML/DL/Python/C++ developer for an INRAE pre-maturation contract for our startup project amineo.design.

The startup's project is to develop, propose and implement digital methods of protein design, in the direction of health (bio-drugs) and green chemistry (without oil,...).

For more information about the position, see

https://amineo.design/docs/Prematuration-position.pdf

Sincerely,

Thomas Schiex INRAE

Hello, You will find attached a job offer CDD of 8 months (2400 euros net / month), in the IRIT laboratory, for a position of Design Engineer in development and deployment of applications.

The person recruited will work in the context of the CRIZ'INNOV project which aims to equip crisis units in the context of natural disaster management.

The development has

two components:

1) optimization of the routes of the emergency vehicles;

spatialized multi-agent simulation (GAMA platform) to visualize the dynamics, impact and possible evolution of a crisis phenomenon.

Host laboratory: Toulouse Computer Science Research Institute (IRIT), teams SMAC and SEPIA

Location: Toulouse 1 Capitole University

Salary: 2400 euros net per month

Duration: 8 months

Expected hire date: January 2022

Keywords: crisis management, GAMA, agent-based simulation, routing algorithms vehicles

Required profile :

• Engineering degree or master's degree in computer science.

• Strong knowledge in object programming and in particular in Java; Python

• Knowledge of Multi-Agent Systems and / or information systems geographic areas would be appreciated.

• Good level of English (especially reading and writing)

Application procedures: submit, before December 20, a CV, a letter of motivation and possibly letters of reference to [email protected] and [email protected]

Sincerely, Chihab HANACHI University Toulouse 1 Capitole Laboratory IRIT

A Postdoc position is open at University of Strasbourg (ICube Laboratory) - France

Deep Learning, Domain Adaptation, Multi-Modal Representations

The position will be funded for two years (initially for one year, renewable for an additional year). The candidate will join the SDC research team under the supervision of Dr Thomas Lampert, the Chair of Data Science and Artificial Intelligence, and join his international team of PhD students and engineer to develop novel deep learning approaches to domain invariant representation learning (particularly in multi-modal data), with application (but not restricted) to Medical Imaging and Remote Sensing.

The funding is not connected to a particular project, so it is the perfect opportunity for a strong candidate to explore new directions under the supervision of the Chair.

The successful candidate will have (or will soon obtain) a PhD in computer science or related domain and have experience in deep learning and applied machine learning and a strong level of written and spoken English.

Experience with transformers, GANs, autoencoders, and/or unsupervised/self-supervised DL (autoencoders, etc) would be a plus. You will join a growing team and will have the freedom to follow your interests in a direction complementary to the abovementioned research focusses.

You will be expected to target leading outlets in the field of machine learning and have a strong track record of publications. Candidates who are able to carry out the highest quality research independently, to co-supervise PhD students, and to give their input on a number of projects being carried out in the team are pursued. You will have access to state-of-the-art hardware for deep learning.

Send a letter of motivation, your CV, and an example publication to Thomas Lamper and Gisèle Burgart ([email protected] [email protected] - !remove the numbers!) with the subject beginning with [Chaire Postdoc].

The position will remain open until a suitable candidate is found and the starting date will be agreed upon with the successful candidate (but can start ASAP).

Detailed Description: https://seafile.unistra.fr/f/5931f91dcffb401db566/?dl=1

KOLOSKOVA Yulia [email protected]

Job: Infolinguist M/F on a permanent contract, Crédit Agricole SA

Position based in Montrouge About Within the Innovation & Digital Transformation division, the Group Data Department aims to maximize the contribution of Data and Artificial Intelligence to the operation of Crédit Agricole.

To this end, it relies on the function of Group Chief Data Officer and the Group DataLab, a reference centre for the internal design of innovative and industrial Data & AI solutions in partnership with Crédit Agricole SA's regional banks, subsidiaries and business lines.

The DataLab Group is organized into 4 specialized teams working on projects within multidisciplinary Squads according to an internal method of Agile inspiration:

Data & AI Engineering aimed at preparing data, defining architectures, infrastructures and "packager" the solutions that will be deployed for integration into the IS

- Analytical and Semantic Data Science, which is an open source-based Artificial Intelligence algorithm using structured data (tabular) and unstructured data (text, image, voice, videos) respectively in order to meet the needs expressed by the business lines of the Group's entities.

Project management that with all the partners and other teams of the DataLab Group, identifies and studies opportunities, frames projects and coordinates their implementation.

Job description Within the Semantic Data Science Team, your main missions will be:

In connection with the Project Managers, support the professions in the expression of their needs, the construction and understanding of the approaches to deal with them,

Lead workshops in particular with the trades in order to build reliable knowledge bases necessary for ai learning and evaluation,

Master annotation methods,

Model and develop natural language processing and machine learning approaches,

Support Data Scientists in the construction of AI, - Collaborate with our Data Engineers and the IT of our partners for the industrial development and production of our solutions

Do scientific monitoring in Artificial Intelligence and identify approaches and tools with high added value for the business

Communicate the results of the work to business and IT experts.

- You come from an Engineering / Master 2 / PhD with a specialization in Machine Learning / AI / Data Science

First successful experience in the implementation of industrial AI solutions in semantic analysis - Minimum level of experience: 2 - 5 years

Mastery of the state of the art in machine learning, natural language processing, annotation and knowledge base building -

Mastery of open-sources in AI and the python development environment -

Computer skills (expected level): Git, Unit Tests, CI/CD, MLOps, docker, python - Knowledge of Agile working methodologies

- Beyond the technical qualities: - Ability to abstract, listen and animate - Fluency in oral and written communication - Interest in crédit Agricole Group businesses.

- Languages: English To apply: send your CV and LM to yulia.koloskova@credit-agricol e-sa.fr

Yulia KOLOSKOVA Infolinguist

ITD/NUM/DTA/DataLab Group/Semantic AI Pole Tel +33 (0)1 43231231

From: François Portet [email protected]

Date: Thu, 25 Nov 2021 11:44:45 +0100

Call for post-doc applications in Natural Language Processing for scientometrics (Grenoble Alps University, France)

Starting date: January. 03, 2022 at the earliest

Duration: full-time position for 24 months (with a possibility of reappointment)

Salary: according to experience (up to 4142€/ month)

Application deadline: Nov 30th, 2021

Location: The position will be based in Grenoble, France. Remote work is partly possible (e.g., 1 day a week).

Keywords: natural language processing, citation classification, citation content/context analysis, scientometrics, name entity recognition, argument mining, transfer learning, deep learning

*Context* The Grenoble Alps University has an open position for a highly motivated postdoc researcher.

The successful candidate will work on the multi-disciplinary ERC Synergy research project NanoBubbles (https://nanobubbles.hypotheses.org) supported by the European Research Council (ERC). The project objective is to understand how, when and why science fails to correct itself. The project’s focus is claims made within the field of nanobiology.

Project members combine approaches from the natural sciences, computer science, and the social sciences and humanities (Science and Technology Studies) to understand how error correction in science works and what obstacles it faces.

For this purpose, we aim to trace claims and corrections in various channels of scientific communication (journals, social media, advertisements, conference programs, etc.) via natural language processing (NLP) techniques.

*Main tasks* The challenge is to build datasets, models and tools that enable analysing how scientific papers are cited, how claims appear in scientific records and are propagated.

This challenge also encompasses the analysis of the rapidly evolving ecology of on-line comments (on post-publication peer-review venues, for instance) complementary to conventional scientific records. The project is interested in hiring people able to contribute to one or more of the following challenges:

- Leveraging existing and developing new NLP methods to retrieve citation contexts, detect citation polarity and build citation network of scientific statements. This means not only counting citations received by a publication but also assessing the content of both cited and citing documents, whether the citation occurs in a scientific paper, a tweet or an on-line comment.

- Leveraging existing and developing new NLP methods to detect, track and identify named entities, claims and counterclaims in scientific publications and social media.

- Take advantage of existing corpus to learn models but also build tools for creation and annotation of new datasets so as to visualise the propagation of claims and counterclaims.

The hired person will interact with PhD students, interns and researchers hired as part of the ERC project. According to his/her background he/she will work in on one or more of the above-mentioned challenges.

The hired post-doc would also be expected to lead the diffusion of corpus collected through open source platforms and/or open shared tasks organisation.

*Scientific environment*

The person recruited will be hosted within the Sigma and Getalp teams of the LIG laboratory (http://sigma.imag.fr/ and https://lig-getalp.imag.fr/), which offers a dynamic, international, and stimulating framework for conducting high-level multi-disciplinary research.

The teams are housed in a modern building (IMAG) located in a 175-hectare landscaped campus that was ranked as the eighth most beautiful campus in Europe by Times Higher Education magazine in 2018.

The person will also be required to collaborate with several teams involved in the ERC Nanobubbles project, in particular with researchers in France from the IRIT lab (Toulouse, France), Ecole des Ponts ParisTech, University of Sorbonne Paris-Nord, CNRS, as well as researchers from in the Netherlands including Maastricht University, Radboud Universiteit and University of Twente.

*Requirements* The ideal candidate must have a PhD degree in Natural Language Processing, computer science.

The successful candidate should have:

- Good knowledge of machine learning techniques

- Good knowledge of Natural Language Processing, previous experience in NER, RE.

- Experience in corpus collection/formatting and manipulation.

- Strong programming skills in Python

- Excellent publication record

- Willing to work in multi-disciplinary and international teams

- Good communication skills

*Instructions for applying*

Applications are expected until Nov 30th, 2021 and must be addressed to Cyril Labbé ([email protected]),

François Portet ( [email protected]),

Frédérique Bordignon ([email protected]).

Applications will be considered on the fly. It is therefore advisable to apply as soon as possible. The application file should contain:

- Curriculum vitae

- References for potential letter(s) of recommendation

- One-page summary of research background and interests

- At least three publications demonstrating expertise in the aforementioned areas

- Pre-defence reports and defence minutes; or summary of the thesis with date of defence for those currently in doctoral studies

Interactive driving simulator for the design of an electric vehicle

Laboratory: LORIA Team: SIMBIOT

Supervisors:

Vincent CHEVRIER vincent.chevrier AT loria.fr

Topic This involves setting up an interactive driving simulator adapted to the needs of the HY2Car project.

Indeed, simulation is an attractive alternative to real experimentation, if only for reasons of cost, time, security, etc.

We therefore want a driving simulator that reproduces the characteristics essentials of the real test vehicle in various situations but also by taking data captured on the real vehicle (repeat in simulation a real route for example).

The idea adopted is to couple a driving simulator (if possible existing) to behavior models energy and mechanics of the vehicle and thus set up a chain of information acquisition, storage and analysis.

The information collected will be used on the one hand to better understand the operation of the electrical source. and decide on optimum vehicle operation and make recommendations to the driver.

A first stage of the internship aims to define the needs of the project, which will make it possible to select a candidate simulator, and ultimately to evaluate the built solution.

The internship will be based on the following steps:

• Definition (with the members of the project) of the information to be collected (vis-à-vis the subsequent analysis steps),

• Definitions of technical criteria characterizing the software solution in terms of use, installation, maintenance, scalability, etc.

• Definition of the desired criteria with regard to the driver's experience (that is to say all the aspects that make that a person will feel comfortable with the simulation and that will lead to a behavior close to what it would be with a "real" car),

• Study of driving simulators offered free of charge (example CARLA https://carla.org/), assessment of their adequacy to needs,

• Selection of a candidate simulator and development of a solution.

Working environment The Hy2Car project brings together different laboratories and university teams. The internship will take place at Loria in the Simbiot team (one of the partner teams of the LORIA project). He is at computer dominant.

However, the recruited person will have to interact with certain researchers from other laboratories than the LORIA (to understand the expectations of the project, see the real vehicle) or other LORIA teams (to integrate the simulator to the existing and to the needs).

Profile expected The successful candidate will have a Master 2 level in computer science or equivalent, skills in integrations software and driving simulator will be an asset.

In view of the interdisciplinary nature of the project, it is desirable to be curious, not to hesitate to question, to know how to work in a team at the interface of several fields and to demonstrate synthesis.

Interested candidates will send a CV accompanied by a cover letter highlighting the match between the subject and the candidate's profile.

Dear All, We are looking for a postdoc to join the research group Marvin (http://marvin.imag.fr/doku. php) at Grenoble University.

Marvin works at the intersection of planning, machine learning and robotics to develop and deploy new algorithms for mission planning for autonomous systems.

The postdoc is for 18 month with possible extension, with an expected start in 2022.

Thank you for contacting me to apply.

Best regards, Damien Pellier

Université Grenoble Alpes Laboratoire d'Informatique de Grenoble

Bâtiment IMAG — 700 avenue Centrale CS 40700 - 38058

Grenoble cedex 9 Office: 365 / Tel: (+33) 4 57 42 15 39http://membres-liglab.imag.fr/pellier

Hello everyone, Two positions for the Programming and Fundamental Computer Science Department of the University of Paris 8 (Saint-Denis, 93) are open for the start of the 2022 academic year:

MCF profile: Artificial intelligence and modeling ( https://informatique.up8.edu/actu/2021-2022.html#mcf2022)

PRAG/PRCE profile: PRAG mathematics option computer science / PRCE digital and computer sciences (https://informatique.up8.edu/actu/2021-2022.html#prag2022)

The recruitment process will follow the schedule of the synchronized session on Galaxie. Feel free to circulate this link to people who might ☺be interested.

Nicolas Jouandeau Director of LIASD University Paris 8

Please send a detailed CV and a cover letter for any application

Type of Contract

Internship then CIFRE thesis or CIFRE thesis directly

Place of work (The time spent in each place will be discussed with the candidate)

● At 55: 5, rue d'Athènes, 75009 PARIS

● AT CRIStAL: Avenue Henri Poincaré, 59655 Villeneuve d'Ascq Modality of the internship

● Remuneration: € 1,200 gross per month (around 1,100 net), Restaurant vouchers + 50% reimbursement of transport tickets + 2 RTT not imposed.

● Train journey between Paris and Lille paid by 55

● Duration of the internship: 5 or 6 months to start as soon as possible

Supervisors

● Philippe Mathieu: Professor and team leader (SMAC) at CRIStAL - [email protected]

● Romain Warlop: Head of Data Science at 55 - [email protected]

Internship subject

We will start the internship by carrying out a bibliographic study on the applications of ABMs in marketing then we will develop in Python a simplified multi agent system in order to study promotion strategies without taking into account the granularity of other marketing levers.

At last we will seek to propose an approach to integrate this use case into the overall model.

For the thesis

We will focus on the following issues:

The creation and management of hybrid systems mixing machine learning, modeling mathematics in the broadest sense, expert human-system exchange tools, ...

Taking into account extremely heterogeneous information, by its nature or by its form, to enrich consumer knowledge, increase the value of the insights generated

3. The explainability of the results and recommendations, the transparency The research work here aims to provide a methodological framework, libraries algorithms or algorithmic schemes that will create, pofor each customer need, a appropriate decision-making solution.

Equally important is flexibility, the ability to evolve with the changes in data sources or activatable marketing levers, but also with the permanent need for functional enrichment.

In addition, brands have seen the complexity and uncertainty of their environment increase over the past few years.

years before reaching the paroxysmal situation resulting from the health crisis of 2020.

The processes current decision-making are too crude, purely empirical or offering only a very limited elements of risk or uncertainty that are measurable, that is to say that are likely to be objective.

However, the need is now to apprehend in a particularly agile way the factors of "radical" uncertainty, almost unique phenomena or for which we have no analogous historical observation.

Candidate profile

● Holder (or in progress) of an M2 computer science or 5th year engineer with high content computer science

● Knowledge of machine learning and data exploitation

● Knowledge of ABM is a plus in the event of an internship and is a prerequisite if there is no traineeship

● Programming language: Python