The COALA team of the Computer Science and Systems Laboratory (LIS) is recruiting a research engineer (renewable one-year fixed-term contract) as part of the Digital Transformation of Maritime Transport (TNTM) project carried out in partnership with the CMA CGM.
Full details are available at: https://www.lis-lab.fr/wp-content/uploads/2022/09/Ingenieur_TNTM.pdf
The Université de Lorraine (France) invites applications for a postdoctoral Researcher in Natural Language Processing and statistical learning for Health.
The position is attached to a new scientific project involving three research units specialized in natural language processing (Research Center for Computer Processing and Analysis of the French Language - ATILF), applied mathematics (Mathematics Research Institute - IECL) and cancer (Research Center for Automatic Control - CRAN).
The main objective is to propose new methodologies and an innovative framework for the development of personalized medicine of low-grade brain tumors based on the latest advances in natural language processing and statistical learning.
The research will investigate methods to automatically retrieve relevant information based on medical data about patients as well as scientific data publications.
The precise research subject within this framework is open to discussion.
Terms and tenure This two-year position will be based at the ATILF, Research Center for Computer Processing and Analysis of the French Language (Nancy, France).
The duration can not exceed 24 months. The ATILF (https://www.atilf.fr/laboratoire/presentation-english/) is a research unit in (computational) linguistics, including expertise in natural language processing and terminology.
Within the framework of multidisciplinary activities, the recruited researcher will be required to interact frequently with two other partner research centers of the project, the IECL and the CRAN, also located in Nancy, as well as to the neuro-oncology department of the regional hospital (CHRU) of Nancy.
The target start date for the position is flexible and depends on the availability of the candidate, in the limit of the beginning of 2023 (to be discussed). Salary depends on experience.
How to apply Applicants are requested to submit the following materials:
- A cover letter applying for the position - Full CV and list of publications - Academic transcripts (unofficial versions are fine)
Applications will be considered as they arise. PhD students planning to defend before the end of 2022 are very welcome.
Applications are only accepted through email.
All documents must be sent to Mathieu Constant ([email protected]), Marianne Clausel ([email protected]) and Hélène Dumond ([email protected]).
Job location Nancy, France
Requirements - PhD in natural language processing, computer science, machine learning or applied mathematics (PhD from the Université de Lorraine are excluded).
Skills - Expert knowledge of Natural language processing - Good knowledge of statistical learning - Good programming skills - Experience in the interaction with biologists and clinicians - Working in a multidisciplinary team
A postdoc on the theme of AMR (Abstract Meaning Representation) is offered by Orange-Innovation. - Duration: 12 months.
- Location: Orange-Innovation, Data and Artificial Intelligence, Lannion (France). - Start: as soon as possible.
Semantic analysis using the AMR representation (Abstract Meaning Representation) makes it possible to obtain interesting results in terms of quality (Smatch/F-measure of 83% for English, 74% for French or Spanish). However, these results are still insufficient to consider exploiting it on languages other than English (when the quality measurement is less than 82%).
Even in English, the good ones scores mask qualitative flaws that remain prohibitive for actual use. Moreover, all the libraries that we tested were too slow for real-time requirements certain application tasks such as question-answering.
Objective of the postdoc: The objective of this post-doc is twofold:
1) Study existing AMR parsing tools and technologies and architectures that they implement in order to establish a policy for improving this parsing.
2) Improve an existing tool or create a new tool to: - Exceed the state of the art in terms of Smatch/f-measurement, especially for languages other than English.
- Reduce the size of the necessary resources (time training, RAM/GPU size).
- Increase inference speed (sentences/seconds).
- Possibly build a multi-tasking model that integrates to the AMR analysis of other tasks (NER/NEL, co-references).
This work will therefore focus mainly on algorithms, but it will also require working on the data.
The main obstacles to overcome are: 1) Obtain an identical semantic graph for expressions semantically identical but syntactically different and different languages.
2) Limit the size of the models.
Your profile : Skills (scientific and technical) and personal qualities required by the position: - Doctoral thesis in computer science with experience in deep learning.
- Knowledge of NLP, particularly on parsing and knowledge of semantics. - Knowledge of Python, PyTorch etc.
- Knowledge of Julia appreciated.
Expected results : - A state of the art on AMR parsing (T0 + 2 months) - A work plan for improving the state of the art (T0+3) - A first monolingual tool for English (T0+6) - A first multilingual tool (T0+12)
Most of the offer You integrate into a research program, one team at a time strongly involved in technology transfer to the teams operations and collaborations with academic teams. For this topic in particular, the team already has experience on AMR (tools, corpus) and will facilitate the appropriation of the subject and your growing competence. In addition, you can count on his support, both scientifically and technically.
If you wish, you can submit the publication of your work, in particular to the communities of NLP.
It would be possible to extend the mission, for example, in order to build a second version of the multilingual tool.
You can submit your application on the Orange Jobs site.
Offer on Orange jobs in French: https://orange.jobs/jobs/v3/offers/115929?lang=fr
Offer on Orange jobs in English: https://orange.jobs/jobs/v3/offers/115929?lang=en
Duration: 2 years Degree required: PhD in Computer Science or Mathematics
Job Description This position is offered as part of a research project whose objective is is to create a data warehouse to integrate and analyze data from project partners related to antibiotic resistance (resistance to antibiotics). The development of the data warehouse is in progress carried out with an engineer from the Zénith team of the Institut national de research in digital sciences and technologies (Inria).
The Zenit team, expert in scientific data management, has a solid experience in the processing and analysis of large amounts of data produced by different methods. After setting up the warehouse, we will need analyze the data to extract new knowledge making the link between human health, animal health and the environment.
For instance the relationship between antibiotic consumption and drug resistance bacteria over time, or the similarity of resistance between man and the animal and the impact of environmental conditions. Among the tracks, we are considering using time series analysis techniques and also big data analysis methods.
The main activities of the recruited person are: • Contribute/supervise the development of the data warehouse to store large volumes of data. • Contribute to the integration of partner data into the warehouse. • Propose and develop new methods for data analysis of antibiotic resistance.
• Evaluate the performance of the proposed methods on the data of the warehouse. • Contribute to the writing of scientific articles for publication in international journals and conferences.
Technical skills and level required: • PhD in Computer Science or Mathematics • Knowledge of data management systems is required. • Experience with data processing infrastructures massive like Spark is appreciated.
Gross salary Between 2500 and 3800 Euros gross monthly (depending on the experience of the candidate).
Workplace Zenith Team, Montpellier
Contact Reza Akbarinia: [email protected] Florent Masseglia: [email protected]
We invite applications for a 3-year PhD position at the University of Lille in the context of the recently funded research project "COMANCHE" (Computational Models of Lexical Meaning and Change). The position is funded by Inria, the French national research institute in Computer Science and Applied Mathematics.
COMANCHE proposes to transfer and adapt neural word embeddings algorithms to model the acquisition and evolution of word meaning, by comparing them with linguistic theories on language acquisition and language evolution. At the intersection between Natural Language Processing, psycholinguistics and historical linguistics, this project intends to validate or revise some of these theories, while also developing computational models that are less data hungry and computationally intensive as they exploit new inductive biases inspired by these disciplines.
The first strand of the project, on which the successful candidate will work, focuses on the development of computational models of semantic memory and its acquisition. Two main research directions will be pursued.
On the one hand, we will compare the structural properties associated to different semantic spaces derived from word embedding algorithms to those found in human semantic memory as reflected in behavioral data (such as typicality norms) as well as brain imaging data. The latter data will then used as additional supervision to inject more hierarchical structure into the learned semantic spaces.
One the other hand, we intend to experiment with training regimes for word embedding algorithms that are closer to those of humans when they acquire language, controlling the quantity as well as the linguistic complexity of the inputs fed to the learning algorithms through the use of longitudinal and child directed speech corpora (e.g., CHILDES, Colaje). In both cases, both English and French data will be considered.
The successful candidate holds a Master's degree in computational linguistics or computer science or cognitive science and has prior experience in word embedding models. Furthermore, the candidate will provide strong programming skills, expertise in machine learning approaches and is eager to work across languages.
The position is affiliated with the MAGNET team at Inria, Lille [1] as well as with the SCALAB group at University of Lille [2] in an effort to strenghten collaborations between these two groups, and ultimately foster cross-fertilizations between Natural Language Processing and Psycholinguistics.
Applications will be considered until the position is filled. However, you are encouraged to apply early as we shall start processing the applications as and when they are received.
Applications, written in English or French, should include a brief cover letter with research interests and vision, a CV (including your contact address, work experience, publications), and contact information for at least 2 referees. Applications (and questions) should be sent to Angèle Brunellière ([email protected]) and Pascal Denis ([email protected]).
The starting date of the position is 1 October 2022 or soon thereafter, for a total of 3 full years.
context The Mediterranean basin is one of the world's 32 hotspots of biodiversity. This thanks, in particular, to the presence of a wide variety of wetlands, considered as the most ecosystems rich and most productive in the region.
However, despite their importance for humans and nature, These environments are also the most threatened by human activities. Indeed, according to a study recent produced by the Observatory of Mediterranean Wetlands (OZHM), it is estimated that Almost half of natural humid habitats have disappeared since the 1970s in this region.
One of the main causes of this rapid decline would be their direct loss, with their conversion towards other forms of soil use. Faced with this alarming situation, it is therefore crucial to gather as much information as possible relevant to the state of Mediterranean wetlands and to analyze the trends of their natural habitats as well as those of the main threats to them.
It is in this context that the OZHM, coordinated by the Valat tower as part of the Medwet initiative, has been developing since ten years an ambitious program to monitor these ecosystems, based on tools and Earth observation technologies (OT). At the same time, new approaches to analyze Satellite images have proven their ability to extract relevant information.
Principally based on deep learning methods (Deep Learning) and for the most recent on the Domain transfer. They allow, for example, to apply models, learned on an area given, on other areas for which there are little or no learning data.
This post of remote sensing engineer proposed here, therefore responds to this need Improvement of knowledge on wetlands using OT tools. It is on the one hand, of Set up a treatment chain based on algorithms developed in collaboration with Various scientific partners of the Valat Tower, such as the ICube laboratory of the University of Strasbourg or the UMR Littoral, Environment, remote sensing, geomatics (letg) of the university Rennes II and, on the other hand, to validate it on real data provided by the OZHM.
The person retained must therefore contribute to the implementation of various projects in progress, notably the project Aionwetlands (supported by the Space Climate Observatory program), as well as a R&D project carried by the Ministry of Ecological Transition and aimed at developing modeling national of wetlands in mainland France and their functions.
Tour du Valat - Le Sambuc 13200 Arles - France I Tel: +33 (0) 4 90 97 20 13 I www.tourduvalat.org
Missions • Contribute, with other technical partners of the Valat Tower, to the implementation tools for analyzing and processing satellite images (essentially optical), especially those incorporating artificial intelligence algorithms (Deep Learning and Machine Learning);
• Extract, using these tools, relevant information on the state and the trends in zones wet followed, their functions, as well as the main pressures they undergo;
• Contribute to the development and application of validation protocols of these results cartographic;
• automate, as much as possible, treatment chains and integrate them into the protocols of Followed by the OZHM, especially in connection with spatialized indicators;
• Contribute, to the development and management of spatialized databases of the OZHM (wetlands monitoring indicators);
• Contribute to the writing of the technical reports of the various projects in which he/she will be involved, in particular the two mentioned above;
• Participate in the development of the various OZHM products, in particular the reports on the State and trends in Mediterranean wetlands;
Profile and skills sought Indispensable : • Bac+5 (m2 or engineer) in computer science, remote sensing or geomatics or any other discipline in environmental sciences integrating a strong component in treatment satellite imaging (geography, regional planning/coastline, ecology, etc.);
• Mastery of GIS tools and processing of Earth Observation Data; • Knowledge of data analysis and learning. A good practice of algorithms Deep learning, without being compulsory, will be an undeniable plus.
• Autonomy, spirit of initiative and good analytical, synthesis and editorial skills; • Ability to work in a team, especially with external partners; • Scientific and communication English in a strongly desired professional environment. Would constitute the assets:
• Knowledge of indicators for monitoring ecosystems (state, trends and pressures); • Mastering statistical tools for data analysis; • Knowledge and/or experience in the Mediterranean; Framing
The Study Engineer will be integrated into the theme team "Dynamic wetlands and water management "and placed under the supervision of the head of the" spatial dynamic axis wetlands ”, Mr. Anis Guelmami [email protected].
Type of contract: The position is to be filled on a fixed -term contract of 18 months. Compensation: € 2,300 at 2600 € gross monthly, according to professional experience.
Posting date: The position is to be filled as soon as possible.
Place of work: Tour du Valat, Le Sambuc, 13200 Arles with the possibility of teleworking 2 days a week.
How to apply Sending candidates to Johanna Perret: [email protected]
(Reference to indicate: TDV-2022-Suivi spatialized ZH) before October 16, 2022, comprising: • A cover letter • A resume • Two referent contacts
The preselected candidates will be summoned for an interview in videoconference or in face -to -face according to geographic constraints.
For any questions about the process of submission of candidates, please contact Johanna Perret [email protected].
We are looking for a Postdoctoral Research Associate: Sensorimotor and brain recovery after stroke.
We are looking for an outstanding and motivated postdoc with a strong interest in neural control of movement and computational neuroscience. The position offers a very stimulating multidisciplinary environment with many opportunities to develop new expertise and conduct independent research.
The post-doc will take a lead role in advancing a project to numerically identify biomarkers of brain plasticity during routine clinical assessments in patients with stroke. A detailed job description and information about the scientific environment can be found at https://dhm.euromov.eu/job-offers/
If interested, please send a CV, statement of research experience and interests, and names and contact information of scientific references directly to PIs.
The post-doctoral project aims to propose an innovative method of interactive multi-paradigm collaborative learning, which combines supervised and non-supervised methods while allowing interaction with the expert.
The candidate will propose and define novel mechanisms that allow supervised and unsupervised methods to collaborate efficiently to reach a classification consensus. The modalities of information exchange between them will have to be specified. He/she will also have to define a protocol for interaction between the user and the learning methods through the use of constraints. Finally, he/she will have to concretely implement the proposed approaches to allow their testing and validation.
Location: Saclay (AgroParisTech campus, 22 place de l'Agronomie, 91120 Palaiseau) (A location at Strasbourg can be discuted) Duration: One year (renewable once) – starting as soon as possible
Salary: between 2500€ and 2700€ before taxes (brut) monthly according to past experience
Contact: Antoine Cornuéjols [email protected] and Pierre Gançarski, [email protected]
EXPECTED PROFILE - PhD in Computer Science and specialized in Machine Learning/Data Mining. - Strong knowledge in Data Science and more particularly in standard classification and clustering methods. Experience in using collaborative/ensemble models or constraint integration would be a plus.
- Good verbal (English or French) and written (English) communication skills. - Interpersonal skills and the ability to work individually or as part of a project team.
TO APPLY Send an email to [email protected] included curriculum vitae, list of publications, letter of motivation and contact details of three references. Applications will be accepted until the position is filled.
Duration: between 16 and 18 months Remuneration: depending on profile and experience, according to the University's salary scale (from 2700 to 3600 € gross monthly).
Position to be filled as soon as possible. The applications will be evaluated as soon as they arrive.
Location: IRIT laboratory, Paul Sabatier University (Toulouse, in France)
Following the ANR DATAZERO [1] project (2015-2019), this position is placed in the context of the ANR Datazero2 (2020-2024). The DATAZERO2 project (a project of the French National Research Agency) in partnership with IRIT (Toulouse), LAPLACE (Toulouse), FEMTO St (Belfort-Besancon) and the industrial partner EATON (Grenoble), aims at improving the operation and design of datacenters operated with local renewable energy sources.
The postdoc will be supervised by IRIT's SEPIA team. The SEPIA team has been working for several years on the optimization of the energy consumption of datacenters.
Research contribution: The project aims to find solutions to operate datacenters powered on only by renewable sources. Different modules are working together to achieve this goal: an IT optimization, an electrical optimization and a negotiation module.
Depending on the profile, experience and interest of the student, two research proposals could be studied:
1) working on the negotiation module. The idea of this module is to find a tradeoff between the power needed to run users tasks and the power available, under uncertainty conditions. Some leverages could be applied on IT applications (postponing, DVFS...) so that the energy budget of the execution could be changed. On the electrical part, storage capacities could also help fit the demand. Different solutions could be envisioned based on a multi-agents approach, game theory, or demand response. A solid work has already been published without considering uncertainty [2].
2) working on IT optimization. During the project, different optimization solutions have been studied by the team: offline IT scheduling under power constraints, online IT scheduling under power constraints. Uncertainties are also currently studied. In the context of this postdoc we would be interested in studying the integration of the datacenter to the city smart grid. An IT optimization could then be studied by considering the energetic mix at different times and trying to minimize the carbon footprint.
Skills, Expected abilities, one or more of the following ● Distributed systems ● Artificial Intelligence, in particular for Optimization, Game Theory, Multi-Agent System, ... ● Fog/Edge computing
Application You can submit your application (CV/Cover Letter) to Georges Da Costa ([email protected]), Patricia Stolf ([email protected]) and Jean-Marc Pierson ([email protected])
Key words: machine learning on time series, clustering, classification, average time series Context Surgical robotics is now widely used with, for instance, more than 5000 Da Vinci systems and one million procedures performed worldwide. Surgery is a complex activity, in a very small anatomical volume, and with a lot of variability between patients and between surgeons. The global objective of the two-year SPARS (Sequential Pattern Analysis in Robotic Surgery: Understanding Surgery) project led by the MediCIS team (LTSI (1), Inserm, Rennes 1 University) is to develop data analysis approaches being able to provide a better understanding of the surgical practice, from complex surgical data. The approaches will be developed thanks to the complementary skills available in the project’s consortium, including time series analysis. In this consortium, the IRISA laboratory (Rennes and Vannes) is calling for applications for a post-doctoral research position (duration two years) on time series analysis.
(1) Laboratoire Traitement du Signal et de l'Image
Missions In the SPARS project context, a trajectory compiles information on the 3D location of the tip of a surgical instrument at the hands of the surgeon, at a constant frequency. The candidate will be mostly involved in one of the three workpackages of the SPARS project. A first task will focus on clustering and classification for such trajectories. Various practical objectives are pursued, including the generation of a model corresponding to a cluster or a class, the characterization of operating modes specific to a type of patient or a type of surgeon, the provision of advice to practitioners in the case of robotic surgeries that are not or not very well documented, the identification of the level of expertise of a practitioner, the prediction of the surgical procedure to be chosen according to the type of patient. These investigations will use dissimilarity measures based on temporal alignment, as DTW [SC71] or elastic kernels as proposed in [CVB07], [CB17] and [M19a]. This task will also address co-clustering for trajectories. The investigations will focus on how to combine time series with other types of data for a co-clustering purpose, using either deep learning [XCZ19] if enough data is available, symbolic representation [BBC15] or latent block [BLN20] models that all need to be adapted to the specificity of kinematics data.
Once a cluster or a class is obtained, another task will be to compute an average trajectory from a set of trajectories. The practical objectives will be the following: highlight deviations from the average trajectory that are potentially interpretable (as characteristics of the practitioner, or of the patient, for example) ; identify the best operating mode to young practitioners or trainees if it is possible to correlate the operating mode with clinical results. Intuitively, on the graphical representation of a time series, variability related to temporality (phase) concerns the abscissa axis, and variability related to shape concerns the ordinate axis. To compute a consensus trajectory, the second task of the package will examine how to extract the atemporal form and the variable component related to temporality, assuming that this atemporal form may be interpreted as an approximation of the consensus. The problem of shape and phase separation has been studied in [PZ16], [SSV10] and [M19a]. The second task will examine how to improve the preliminary work in [M19b], notably by proposing other kernels.
Requirements for this position Doctorate in computer science, applied mathematics and computer science, or mathematics, with a specialization in machine learning and the following requirements:
- theoretical skills and experience in probability / statistics, applied mathematics, machine learning,
- strong knowledge and solid experience in temporal data analysis,
- publications in major conferences or journals in the field,
- mastery of data manipulation, relying on machine learning libraries,
- programming experience, good programming skills (notably in Python) and technical ability to manage a code development project,
- ability to work in a team, and report on the progress of work.
Some knowledge in deep learning will be a plus.
The personal qualities expected are mostly autonomy and interest in interdisciplinarity (health), as well as writing skills (both in French and English). Fluency in French will be a plus.
Work environment Location: Institut de Recherche en informatique et Systèmes Aléatoires (IRISA), Université de Rennes 1 - Campus Beaulieu, 263 Av. Général Leclerc, 35000 Rennes
Duration: 24 months – Applications will be accepted until the position is filled (for recruitment by 1 December 2022 at the latest)
Host team: LINKMEDIA
The successful candidate will work with four academic researchers from IRISA / Rennes / LINKMEDIA team (Simon Malinowski, Associate Professor in Computer Science), IRISA / Vannes / EXPRESSION team (Pierre-François Marteau, Full Professor in Computer Science), LS2N (2) / Nantes / DUKe team (Christine Sinoquet, Associate Professor with French Accreditation to supervise Research (HdR)) and INSERM / Rennes / LTSI MediCIS team (Pierre Jannin, Directeur de recherche INSERM, HdR). The successful candidate will collaborate with the partners in the project, among which the other post-doctoral fellow involved in the project and the project partners experts in surgery and in surgical data analysis.
(2) Laboratoire des Sciences du Numérique de Nantes : UMR CNRS 6004
Income: 2160,26 euros before taxes monthly
How to apply? Documents to be provided :
- detailed Curriculum Vitae including a complete list of publications,
- letter of motivation indicating the candidate’s research interests and achievements to date,
- a selection of publications,
- the PhD thesis manuscript,
- Master 2 marks (with rank and number of students in the year)
- letters of recommendation for the current year,
- contact details of two referees (at least) with whom the candidate has worked (first name, surname, status, institution (give details of acronyms if applicable), city, e-mail address, telephone number)
Questions or application files (zip archive only) should be sent to the four contact persons below:
[email protected] [email protected] [email protected] [email protected] (SPARS project leader)
Simon Malinowksi http://people.irisa.fr/Simon.Malinowski/ Christine Sinoquet https://christinesinoquet.wixsite.com/christinesinoquet Pierre-François Marteau https://people.irisa.fr/Pierre-Francois.Marteau/ Pierre Jannin https://medicis.univ-rennes1.fr/members/pierre.jannin/index
As part of the ANR D4R project ( https://d4r.hypotheses.org/ ) which is in the field of digital humanities, we are looking to fill a position as a computer scientist specializing in one or more of the following fields: artificial intelligence , data mining and machine learning.
Some info: - The position is located in Toulouse at IRIT on the Paul Sabatier University campus.
- The contract will ideally start on January 1, 2023 for a period of 16 months.
- Supervision will be carried out by Pr Josiane Mothe and David Panzoli
We are looking for a candidate for *a post-doctoral contract in NLP*.
The work will be carried out within the Corpus Dynamic Models Laboratory (MoDyCo, UMR 7114) and at the Architecture City Urbanism Laboratory Environment (LAVUE, UMR 7218). Funding will be provided through of the VITAL project (City, Automatic Language Processing).
*Key terms:*urban planning, architecture, TAL, spatial dynamics, project urban, urban change, discourse of city specialists
*GOALS* The VITAL project brings together researchers in an original and innovative way automatic language processing (TAL), architects and town planners, in a partnership research project with the National Archives and in collaboration with other institutions. This project aims to understand how speeches and architectural projects and urban people approach space as a dynamic and to study how expresses this dynamic.
The interdisciplinary approach adopted here mobilizes the TAL in order to identify and analyze the elements of the discourse reflecting the notion of urban dynamics and its perception by specialists in the field of urban planning in development projects and initiatives. It is test the feasibility and reliability of a linguistic analysis automatic expressions referring to dynamics in the domain of urban planning as well as to propose a modeling of the phenomena sought and a typology of markers characterized by the associated properties.
*INFORMATION CONCERNING THE DOCTORAL CONTRACT* - Duration: 8 months with possible extension of 1 month.
- Start of the contract: January 1, 2023
*REQUIRED PROFILE* Candidates must hold a doctoral thesis in automatic processing of natural language or in tooled linguistics and show an interest in the field of urban planning. Autonomy in coding in python is essential, as well as basics in machine learning.
*FRAMING* The postdoctoral fellow will be co-supervised by the Professors Iris ESHKOL-TARAVELLA (/Doctoral School/n°139 “ Knowledge, Language, Modeling”, PR specialist in NLP) and Olivier RATOUIS (ED 395 doctoral school - Espaces doctoral school, Time, Cultures, PR Urbanism)
*HOW TO APPLY* Candidates who wish to apply for this post contract must provide a file consisting of the following documents:
1. An academic curriculum vitae (2 pages maximum);
3. A cover letter (3,000 characters maximum);
4. Letters of recommendation
5. Thesis reports if possible
The application file will be sent in electronic form in the format .pdf (a single file with the name of the candidate) on the addresses following: [email protected] , [email protected]
*CALENDAR* - Sending of application files: from Monday, September 5, 2022
- Deadline for submitting applications: Friday, December 2, 2022 at 5:00 p.m. (Paris time)
- Selection of candidates: between December 5 and December 16, 2022
- Announcement of results: December 19
- Taking office: January 1, 2023
*CONTACT* Iris Eshkol-Taravella ( [email protected] ), Olivier Ratouis ( [email protected] )
We are looking, as part of the ANR CODEINE project, for a cross-platform developer on an 18-month developer CDD two games with one goal:
https://www.univ-lorraine.fr/travailler-al-ul/offre-emploi/developpeur-plateforme-hf/
The position will be located at LORIA, in Nancy.
Feel free to circulate the offer.
It is possible to contact me directly to apply (do not hold account of the date indicated on the advertisement).
LISN is recruiting a one-year post-doc as part of the ANR GEM project (Gender Equality Monitor) on identifying gendered expressions by vector representations on a transcription corpus of speech in the media.
the offer is detailed below:
Post-doctorate (M/F) Identification of gendered expressions by vector representations on a transcription corpus of the speech in the media
General informations Reference: UMR9015-CYRGRO-002
Place of work: ST AUBIN
Publication date: Saturday September 10, 2022
Type of contract: Scientific CDD
Contract duration: 12 months
Expected date of employment: December 1, 2022
Work shift: Full time
Remuneration: Between €2889.91 and €4082.9 gross per month depending on experience
Desired level of study: PhD
Desired experience: 1 to 4 years
Tasks The GEM (Gender Equality Monitor) project aims to analyze the interactions between women and men in the media (radio and television), and more particularly the differences in representations depending on whether the person speaking is a woman or a man, according to his role (anonymous, journalist, politician, etc.), and according to the themes.
In this interdisciplinary project, the partners (including LISN) are responsible for implementing the descriptors that will allow partners in the human sciences and to quantify and qualify differences in representation. https://anr.fr/Projet-ANR-19-CE38-0012
Activities The recruited person (M/F) will be in charge of developing unsupervised automatic language processing (TAL) techniques or semi-supervised applied to corpora of transcriptions automatic speech, to identify "gendered expressions" such as references to cultural stereotypes based on the gender, traditional named entities or any reference to life privacy, age, physique, sexuality, skills, etc. Secondarily, the analysis of biases in language models can also be driven.
The corpora are made available by the project leader (Institut National de l'Audiovisuel) and consist of: morning radio and television logs from the GMMP corpus (Global Monitoring Media Project), French radio programs (cooking shows, economic, sporting, and free-to-air) for the study of incivilities (interruptions, insults, etc.), and reality TV shows (Loft Story 2001, The Marseillais in Dubai 2021). No annotation is available around gendered expressions. The recruited person must therefore favor unsupervised or semi-supervised methods.
This work will be co-supervised by Ms. Sahar Ghannay (MCF in computer science at Paris Saclay University) and Mr. Cyril Grouin (IR in computer science at CNRS). The contract will be funded by the National Research Agency (ANR GEM 2019) led by David Doukhan (National Institute of Audiovisual).
Skills - very good command of French - automatic language and speech processing; a training specific in this discipline is a plus - experience of lexical embeddings and neural networks
Work context The Interdisciplinary Laboratory of Digital Sciences (LISN) is a unit installed on the Saclay plateau and created in 2021 from the merger of LIMSI and LRI laboratories. Research carried out at LISN cover a broad scientific spectrum and are recognized the international.
The laboratory includes more than 380 members divided into 16 teams of research and 6 support services and support. The premises are entirely in a restricted regime zone (ZRR).
The recruited person will work within the ILES team, in connection closely with the researchers from the ILES and TLP teams involved in the project, within the Language Sciences and Technologies department (STL).
Constraints and risks - Travel possible in Ile-de-France for work meetings punctual - National and international travel in conference in case of article to present - Computer work
Apply here: https://emploi.cnrs.fr/Offres/CDD/UMR9015-CYRGRO-002/Default.aspx