PSL University is hiring: 1 junior data-scientist for social sciences https://acss-dig.psl.eu/en/candidate?tab=2
He/she will join our team of data scientists: https://acss-dig.psl.eu/en/equipe and will work in a multidisciplinary environment of social scientists/computer scientists and mathematicians:
https://acss-dig.psl.eu/en/membres
Application form: https://acss-dig.psl.eu/en/candidate?tab=3
Université PSL is recruiting: 1 data science engineer for the social sciences https://acss-dig.psl.fr/en/candidate?tab=1
He/she will join our team of data-scientists: https://acss-dig.psl.eu/fr/equipe and will work in a multidisciplinary environment composed of researchers in social sciences / computer science and mathematics:
https://acss-dig.psl.eu/fr/membres
To apply: https://acss-dig.psl.eu/fr/candidate?tab=3
Positions : Engineer, Full time
Start date : as soon as possible
Duration : 6 months
Indicative salary : depending on experience from 1,980 Euros to 2,320 Euros net per month (2,460 Euros to 2,890 Euros gross per month) with social benefits
Host laboratory : Aix-Marseille University, Marseille, LIS Lab (CNRS UMR 7020), Luminy site, France
How to apply : Email your complete CV including projects already completed to [email protected] and [email protected]
The work will be carried out as part of the multi-partner QualiHealth project funded by the ANR.
The candidate will participate in the extension of a data science platform dedicated to improving the quality of health data.
* The successful candidate will work on the development of applications: redesign of an application, implementation of new algorithms on health data. More specifically, the main missions are:
Redesign of an application for data quality profiling (java);
Prototype refactoring (C++);
Integration and interfacing with the health data quality control platform.
* Profile required:
BAC +5 in computer science Full stack java development experience Programming skills in Python and C++ Skills in test campaign.
Applications are invited for a full-time Post-doctoral Research Fellow (PDRF) position in deep learning (Graph Neural Networks) for the early detection of lung cancer funded by Cancer Research UK, with project partners at the University of Liverpool.
The PDRF will work on an exciting, cross-disciplinary collaborative project to develop advanced computational models to discover the evolving latent structures representing relationships/patterns in multimodal data linking to lung cancer.
The detailed application procedure can be found here (Deadline: 16 October 2022): https://jobs.edgehill.ac.uk/vacancy.aspx?ref=EHR0111-0922
Informal enquiries may be addressed to [email protected]
Dear colleagues, I am recruting a new postdoc for the ARIAC project supported by Digital Wallonia.AI and the SPW Recherche that gathers tens of researchers accross Wallonia in artificial intelligence.
Keywords: robustness, stability, constraints, information visualisation, interaction, interpretability, explicatblity, etc.
Deadline: 15th October.
She/he will do research in the "trust mechanisms for AI" workpackage and help me to lead this workpackage. She/he will be integrated in the Human Centered Machine Learning (HuMaLearn - https://humalearn.info.unamur.be) team at UNamur with around 10 other PhD and postdoc researchers and she/he will have collaboration opportunities thanks to the interdisplinary approach of ARIAC and of HuMaLearn.
Please spread the work and do not hesitate to contact me for further details.
https://euraxess.ec.europa.eu/jobs/844078 https://jobs.unamur.be/emploi.2022-09-13.7042797172/view
Start date : as soon as possible
Duration : 6 months
Indicative salary : depending on experience from 1,980 Euros to 2,320 Euros net per month (2,460 Euros to 2,890 Euros gross per month) with social benefits
Host laboratory : Aix-Marseille University, Marseille, LIS Lab (CNRS UMR 7020), Luminy site, France
How to apply : Send your complete CV including a complete list of publications (and if possible a link to your thesis) by email to [email protected] and [email protected]
The work will be carried out within the framework of QualiHealth, a multi-partner project funded by the ANR.
The candidate will participate in the extension of a data science platform dedicated to improving the quality of health data.
* The successful candidate will work on the development, implementation and application of machine learning algorithms and approaches to improve the quality of health data. More specifically, the main missions are:
Research on healthcare data quality profiling and knowledge graph; Design machine learning algorithms to discover and classify data quality rules, dependencies and constraints;
Prototyping and testing solutions for learning data quality indicators and quality constraints;
Integration and interfacing with the health data quality control platform.
* Profile required: PhD in Computer Science Experience in machine learning and/or complex data analysis and/or data management
Programming skills in Python Good written and verbal communication skills in English
Location: Clermont-Ferrand, France Host institutions: Institut Pascal and the city hospitals of Clermont-Ferrand and Saint-Etienne
Starting Date: when student found
Funding Duration: 3 years
Supervisors: Dr. Erol Ozgur, Dr. Mohammad Alkhatib, Prof. Adrien Bartoli, Prof. Youcef Mezouar.
Application Deadline: Open until filled
Project: This position will be funded by IMMORTALLS, an ANR-JCJC project. Context: Liver cancer is a leading cause of cancer death worldwide. An estimated 830,000 people around the world died from the disease in 2020.
Liver resection is considered as one of the most effective treatments. In this respect, laparoscopic liver resection (LLR) comes up by reducing substantially patient trauma compared to open liver resection.
The patient recovers faster which in return reduces healthcare costs. However the use of LLR remains limited. This is because of three challenges. First, controlling intraoperative bleeding using laparoscopic instruments requires advanced technical skills.
Second, the surgeon cannot manually palpate the liver and thus cannot locate the tumours and their resection margins easily.
Consequently this raises a risk of inadequate resection on the patient’s liver such as the removal of too much healthy tissue and the leaving of some cancerogenous tissue behind.
Third, laparoscopic ultrasonography (LUS), the only tool for intraoperative subsurface imaging which allows real-time tumour localisation, has a long learning curve.
This is because its design consists of a small transducer with a small field of view attached to the end of a long shaft with a pivoting mechanism.
In order to ease LLR, augmented reality (AR) based methods relying on preoperative data were proposed [1,2].
These AR-based methods predict the location of the tumours by overlaying the preoperative data onto the laparoscopy image.
These methods require the whole liver to be visible as much as possible in the laparoscopy image to make a reliable prediction.
However, the liver is usually very partially visible (i.e., about 30% or less). Although these methods are useful to guide surgeons at the very beginning of surgery, they are neither real-time nor automatic.
[1] “Combining Visual Cues with Interactions for 3D-2D Registration in Liver Laparoscopy”, Annals of Biomedical Engineering, 2020.
[2] “Augmented Reality Guidance in Laparoscopic Hepatectomy with Deformable Semi-automatic Computed Tomography Alignment”, Journal of Visceral Surgery, 2019.
Links: http://igt.ip.uca.fr/~ab/ https://erol-papers.github.io
Research: We are looking for one highly motivated PhD student to study on multimodal liver tumour registrations and augmentations
to be able to guide the surgeons during LLR. The PhD student will focus on two open problems.
1/ Automatic and real-time deformable registration of a preoperative CT volume to an intraoperative LUS image without any additional tracker sensor.
2/ Augmentation of the subsurface liver tumours and veins in the laparoscopy images (i.e., occluded object visualisation) on a flat screen with the relevant depth cues such that their depth can be conveyed to the surgeon accurately.
The successful outcome of the PhD will simplify mini-invasive liver surgery. It will shorten hospital stays, improve surgical safety and accuracy, and contribute to
an overall better quality of patient life and reduction of healthcare costs.
Requirements: 1/ undergraduate and graduate degrees on Computer Science or closely related fields;
2/ excellent programming skills in C++ and python;
3/ strong theoretical and applied background in computer vision and machine learning;
4/ experience in augmented reality;
5/ proficiency in written and spoken English language.
Application: Applicants must submit
1/ a one-page cover letter, 2/ curriculum vitae with publications list and contacts of 2 references, 3/ a copy of academic transcripts (bachelor/master grades), 4/ availability (the earliest possible starting date).
Applicants must be prepared to provide two reference letters upon request. Once we receive your application and it fits well to the position, you will be contacted within two weeks.
Applications should be sent, *in a single PDF document*, with the email subject [IMMORTALLS PhD application] to:
[email protected]; [email protected]; [email protected]; [email protected]
The Institute of Creative Media Technologies (ICMT) at the University of Applied Sciences in St. Pölten, Austria invites applications for two pre-doc positions in the field of Machine Learning, Computer Vision and Visual Analytics with an interdisciplinary focus on research questions from the Digital Humanities: https://www.fhstp.ac.at/de/offene-stellen-karriere/junior-researcher-fuer-computer-vision-machine-learning-im-kulturellen-kontext-40-h-304988 (see also attached PDF)
The position’s contract length is unlimited and optionally part-time. You will work on challenging research topics on Computer Vision, Machine Learning, Multimedia Retrieval and Visual Analytics together with researchers from the cultural humanities (film studies and art history). The positions are supported by interdisciplinary basic research projects funded by national funding organizations in Austria (FWF, GFF). With your contribution you will support the further growth of our research group and the definition of new research directions. See here for an overview of our projects and research topics: https://icmt.fhstp.ac.at/en/projects?filter-hashtag=Artificial+Intelligence
We expect a strong research oriented background on machine/deep learning and multimedia analysis, excellent programming skills, team spirit and ideally first publication experience.
All genders are welcome to apply. We explicitly encourage people with disabilities to apply.
For informal questions, you can contact Matthias Zeppelzauer ([email protected]).
Lingua Custodia is a Fintech company leader in Natural Language Processing (NLP) for Finance. It was created in 2011 by finance professionals to initially offer specialised machine translation.
Leveraging its state-of-the-art NLP expertise, the company now offers a growing range of applications in addition to its initial Machine translation offering: Speech-to-Text automation, Document classification, Linguistic data extraction from unstructured documents, Mass web crawling and data collection, ... and achieves superior quality thanks to highly domain-focused machine learning algorithms.
Its cutting-edge technology has been regularly rewarded and recognised by both the industry and clients: Investment houses, custody or investment banks, private banks, financial divisions within major corporations and service providers for financial institutions.
Lingua Custodia’s team is composed of a diversified mix of profiles, strongly skilled in their area of expertise, all committed to our entrepreneurial adventure. But what we value the most at Lingua Custodia are soft skills: Team spirit, trustfulness, open-minded thinking, enthusiasm, freedom to try new ideas or practices
***Responsibilities***
The NLP researcher will be part of the R&D team. He/she will design and implement experiments in the field of Neural Machine Translation, which will be reported in scientific, technical publications and demonstrators at international conferences (WMT, EAMT, ACL, EMNLP).
Research activities relate mainly to the following topics:
- Automatic data extraction and cleaning methods - Bilingual Terminology induction from monolingual data - Terminology control in Neural Machine Translation to ensure the reliable translation of specific entities - Modelling of source sentence coverage during translation - Document-level Machine Translation - Machine Translation evaluation
***Qualifications***
- PhD in Computer Science, Machine Learning, Natural Language Processing or any related fields. - Strong track record of successful implementations and publications in Natural Language Processing or Machine Learning. - Experience in Linux environment: Bash scripting.
- Proficiency in Python - Proficiency in at least one neural framework: TensorFlow, Pytorch, etc - Bilingual or high proficiency in French
***Benefits***
- Friendly start-up environment - Laptop - Possibility to work remotely - Health insurance - Lunch vouchers
***Contact***
Applications are expected by email: [email protected] Please, specify the position name in subject field.
*Location*: Inria Rocquencourt or Saclay (Paris region)
*Dates*: position to be filled as soon as possible, for a period of 2 years
*Context* This post-doctorate is part of the CLEE project (High Energy Liquid Fuels), set up in partnership by the start-up Alysophil, the company MBDA and the Defense & Security department of Inria.
The objective of the CLEE project is to develop new fuels offering better performance, for example in terms of their viscosity, density, calorific value, etc., thus allowing greater autonomy at reduced volume, or reducing the environmental footprint. production units. In order to identify new candidate molecules to be evaluated, the approach explored is their generation by artificial intelligence.
To describe a molecule, different encodings make it possible to represent it in the form of a string of characters (eg: SMILES, SELFIES languages, etc.). The hypothesis that motivates this post-doctorate is therefore that approaches derived from natural language processing can be generalized to the analysis and generation of molecules.
The post-doctoral student will work under the supervision of Lauriane Aufrant (researcher responsible for language activities at Inria Defense & Security), and in close collaboration with industrial partners.
*Required profile* - Holder of a doctorate in automatic natural language processing or deep learning, or preparing to support
- Theoretical and practical knowledge of Transformer models, comfortable with model training
- Experience on at least one of the following topics: semi-supervised learning, data augmentation, information extraction in scientific texts, reinforcement learning
- Willingness to diversify skills by applying known algorithms to new areas - Strong interest in collaborative and multidisciplinary work
*To apply* Send CV and cover letter to lauriane.aufrant at inria.fr and frederique.segond at inria.fr
Letters of recommendation or indications of references would be appreciated but are not mandatory.
*Work description* The post-doctorate will initially focus on the analysis of existing molecules (prediction of properties: viscosity, density, etc.), in order to identify the optimal architecture for the processing of SMILES or SELFIES encodings. The first avenue to explore relates to Transformer-type architectures, but other approaches may be considered depending on the results obtained. The scientific challenges to be met include in particular the choice of the input representation of the model (e.g. experimentation with CharacterBERT type architectures) and the low volume of existing datasets (e.g. experimentation with data augmentation methods, transfer, semi-supervision, etc.).
In order to compensate for the lack of data, and depending on the results obtained on pre-existing data, it is planned to resort in parallel to more exploratory approaches to collect new data (molecules and/or properties), such as extraction of information from scientific publications.
In a second step, the work carried out on the prediction of properties will be enhanced to move on to the generation of new molecules under the constraint of desired properties. Other algorithmic approaches will then have to be implemented in conjunction with the architecture initially selected for the analysis. Various avenues can be explored, including GANs, VAEs, graph grammars, reinforcement learning, genetic algorithms, etc.
Throughout the work, the post-doctoral student will be able to benefit from the expertise in fuel chemistry provided by the partner companies, in order to focus on the algorithmic aspects of the project. The final validation of the new molecules proposed will be carried out manually by expert chemists.
We invite applications for a 3-year PhD position co-funded by Inria, the French national research institute in Computer Science and Applied Mathematics, and LexisNexis France, leader of legal information in France and subsidiary of the RELX Group.
The overall objective of this project is to develop an automated system for detecting argumentation structures in French legal decisions, using recent machine learning-based approaches (i.e. deep learning approaches). In the general case, these structures take the form of a directed labeled graph, whose nodes are the elements of the text (propositions or groups of propositions, not necessarily contiguous) which serve as components of the argument, and edges are relations that signal the argumentative connection between them (e.g., support, offensive). By revealing the argumentation structure behind legal decisions, such a system will provide a crucial milestone towards their detailed understanding, their use by legal professionals, and above all contributes to greater transparency of justice.
The main challenges and milestones of this project start with the creation and release of a large-scale dataset of French legal decisions annotated with argumentation structures. To minimize the manual annotation effort, we will resort to semi-supervised and transfer learning techniques to leverage existing argument mining corpora, such as the European Court of Human Rights (ECHR) corpus, as well as annotations already started by LexisNexis. Another promising research direction, which is likely to improve over state-of-the-art approaches, is to better model the dependencies between the different sub-tasks (argument span detection, argument typing, etc.) instead of learning these tasks independently. A third research avenue is to find innovative ways to inject the domain knowledge (in particular the rich legal ontology developed by LexisNexis) to enrich enrich the representations used in these models. Finally, we would like to take advantage of other discourse structures, such as coreference and rhetorical relations, conceived as auxiliary tasks in a multi-tasking architecture.
The successful candidate holds a Master's degree in computational linguistics, natural language processing, machine learning, ideally with prior experience in legal document processing and discourse processing. Furthermore, the candidate will provide strong programming skills, expertise in machine learning approaches and is eager to work at the interplay between academia and industry.
The position is affiliated with the MAGNET [1], a research group at Inria, Lille, which has expertise in Machine Learning and Natural Language Processing, in particular Discourse Processing. The PhD student will also work in close collaboration with the R&D team at LexisNexis France, who will provide their expertise in the legal domain and the data they have collected.
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 Pascal Denis ([email protected]).
The starting date of the position is 1 November 2022 or soon thereafter, for a total of 3 full years.
We are looking for a postdoc and a PhD to work on interpretable computer vision methods for species identification by making explicit use of morphological traits. For the full decription:
Postdoc: https://jobs.inria.fr/public/classic/en/offres/2022-05288
PhD: https://jobs.inria.fr/public/classic/en/offres/2022-05289
Diego Marcos gonzalez [email protected]
recruit an engineer (1 year fixed-term contract, possibly 2 years) to work on the production of a glove allowing interaction by micro-gestures, as well as the production of a demonstrator showing the use of this glove in different contexts.
To apply, contact us directly by email, attaching CV and cover letter.
Do not hesitate to write to us if you have any questions and/or to distribute this offer to anyone potentially interested.
Alix Goguey and Laurence Nigay [email protected] [email protected]
Job description
Your mission will be to develop a robust glove prototype allowing human-machine interaction by micro-gestures (gestures of the fingers of the hand). Initially, the mission will consist in identifying a technical solution which will be the basis of the recording. Several prototypes have already been made, each prototype exploring a different capture solution. You will have access to all of our work already carried out and will work in collaboration with a team of researchers who have acquired expertise in this field. In a second step, the mission will consist in making several copies of a glove implementing the chosen technical solution, with the objective of a level of maturity TRL 4. It is envisaged to file a patent on the realized capture system.
Main missions :
- Study of possible technical solutions
- Realization of a glove allowing the capture of micro-gestures - Realization of a software layer allowing the use of micro-gesture events captured by the glove
- Realization of a demonstrator illustrating the use of micro-gestures in various applications.
Required skills:
- Electronics - IT development - Excellent material and manufacturing skills
Profile : - You hold a Bac+5 diploma in Electronics or Computer Science (Engineering School or University)
- Quality: Autonomy, ability to work in a team, appetite for research in the service of users.
- All applications are welcome, regardless of age, gender identity, social or ethnic origin, sexual orientation or disability.
Remuneration: - for a beginner engineer, the monthly gross salary could be between 1985 and 2300 €
- for a more experienced engineer, the gross monthly salary could be between 2288 and 3200 €
Company : Floralis, a subsidiary of the University of Grenoble Alpes (100 p. > 10 M€ turnover) works on the development and transfer of new technologies from research laboratories and the management of industrial relations of research laboratories and in particular ensures the mission of operator of the Carnot Software and Intelligent Systems Institute (iC LSI).
As part of the project entitled "iGlove" led by the Carnot Software and Intelligent Systems Institute, we are recruiting a Design Engineer who will work within the IIHM (Engineering of Human-Machine Interaction) research team of the laboratory. LIG, located on the Saint-Martin-d'Hères university campus.
Developing systems towards robust discourse parsing and its application
https://pagesperso.irit.fr/~Chloe.Braud/andiamo/
* Contract duration: 12 months (flexible)
* Starting date: December 2022 (flexible)
* Location: IRIT, Université P. Sabatier (Toulouse III)
* Remuneration: starting at 2,745 euros, gross salary, depending on experience
* Application deadline: the position will be open until fulfilled
* Send application by email to [email protected]
Application procedure: please send a CV and a short letter motivating your application by detailing the following elements:
* indicate your **skills in machine learning**, e.g. the type of tasks you already worked on, the type of algorithms, the libraries used. Please specify your experience with neural architectures and pre-trained language models.
* describe your **interest and/or experience in natural language processing**, i.e. the type of tasks you already tried to solve if any, or similar problems you worked on, or why you now want to work in NLP and why you think your experience in another domain could be relevant
* If you are interested but don’t have a phd, rather a master / engineer diploma and your CV fits the requirements, please send me an email with the same information as above
Incomplete application will not be considered.
The AnDiAMO project: Natural Language Processing (NLP) is a domain at the frontier of AI, computer science and linguistics, aiming at developing systems able to automatically analyze textual documents. Within NLP, discourse parsing is a crucial but challenging task: its goal is to produce structures describing the relationships (e.g. explanation, contrast...) between spans of text in full documents, allowing for making inference on their content. Developing high-performing and robust discourse parsers could help to improve downstream applications such as automatic summarization or translation, question-answering, chat bots, e.g. [1,2,3]. However, current performance are still low, mainly due to the lack of annotated data (see e.g. [4] on monologues, [5] on dialogues, [6,7] for the multilingual setting).
In order to develop robust discourse parsers within the AnDiAMO project, we want to explore multi-objective settings, where the goal is ultimately to perform a discourse analysis, but relying on another related objective such as performing well on another task (e.g. morphological, syntactic or temporal analysis), or an application (e.g. sentiment analysis or argument mining). We will also explore the issues of cross-language and cross framework learning.
The position is funded by the ANR AnDiAMO project, for which an engineer has already been hired, master interns will also be recruited. Collaborations are planned with researchers in Toulouse, Grenoble, Nancy and Munich. The hired person will be part of the MELODI team at IRIT, participating in team and project meetings, and co-authoring articles.
Research plan: The recruited candidate will work on one or several of the following topics, depending on its interests:
- Data representation: Discourse processing requires information from various levels of linguistics analysis. For now, existing studies do not make it clear what kind of information is important and needed, and some potentially relevant sources of information are ignored. We plan to explore this issue within a multi-task learning setting, where a system has to jointly learn different tasks. We will experiment on classification tasks (discourse relation, segmentation) and on full discourse parsing.
- Transferring to new languages, domains and modalities: Developing systems that perform well on domains or languages that are different from those used at training time is crucial, especially if the adaptation can be done in an unsupervised way. It is especially important for discourse, since annotation is very hard and time-consuming. We plan to experiment with cross-lingual embeddings and to explore multi-task learning, but trying to understand how to integrate additional linguistic information with only little annotated data for auxiliary tasks. We also want to investigate dialogues, for which only a few discourse parsers exist, and better understand how it differs from monologues.
- Extrinsic evaluation: We will investigate a few downstream applications that could benefit from discourse information, as a way to give an extrinsic evaluation. We will explore pipeline systems, varying the way we encode the discourse information as input of our end system. We will also explore transfer learning strategies, either via multi-task learning or representation learning. We plan to start with cognitive impairment detection (e.g. schizophrenia, Alzheimer) and argument mining. More applications will be considered, depending on the interest of the recruited postdoc.
It will be possible to investigate other paths of research, such as few-shot or unsupervised learning, depending on the interest of the recruited candidate.
Profile * PhD degree in computer science or computational linguistics
* Good knowledge in Machine Learning is required
* Interest in language technology / NLP
* Good programming skills: preferably with Python, knowledge of PyTorch is a plus
Duration of the contract (if open to contractors): 18 months
Job Information
For more information on the position, do not hesitate to contact Mrs. Marie-Pierre Gleizes: Marie- [email protected])
Salary: civil service salary scale (2038€ gross per month for a beginner IR) Sending applications
CV and cover letter to be sent exclusively to the following address:
Our world is facing unprecedentedly severe social and environmental crises.
The scale of the response requires deep and efficient _coordination_ of resources and efforts.
The CEA is a French public research institution with strong ties to the industrial ecosystem and European institutions. It constitutes the ideal setting to agilely build, test and implant the necessary digital supporting foundations for wide scale inclusive interdisciplinary coordination.
Our group is part of the CEA Tech. It designs and develops tools for a wide variety of engineering applications in a wide variety of domains. We are equipped with long-standing experience and expertise in tailoring, developing, optimising, interfacing and integrating open source and proprietary software solutions for our various clients, both public and private.
We wish to hire a new team member to come and work with us on our coordination solution, to architecture the system’s foundations, set them up and test them in diverse use cases.
** Job description: **
18 months, full-time research engineer at the CEA-Tech in Palaiseau (plateau de Saclay, Île-de-France).
We are looking for a research engineer to participate in the development of a collaborative digital platform implementing principles of collective intelligence. The role is a hands-on opportunity to contribute at the centre of an exciting, meaningful, avant-garde project, empowering coordination across engineering domains and solutions and scientific disciplines and research.
** Core responsibilities: **
- Participate in the architectural design of a complex distributed system - Design and develop a web-based system (front-end and back-end) that accesses and manages large datasets
- Write technical documentation of software and solutions - Support all activities related to end to end software design and testing - Fit in with the development team and interact with cross-functional teams
** Requirements & Qualifications: **
- Programming languages: C, C++, Rust or Java - Knowledge of one or several DBMS - Experience with version control technology (e.g. Git)
- Basic knowledge of RESTful architectures and implementations - Fluent in English and/or French - Proactive work ethics
- Attention to detail and excellent analytical skills (profound algorithmic and complex architectural decisions will be involved) - Engaging entrepreneurial personality, interested in broadening your horizons and expanding your skills to master new technologies and new perspectives.
** Plusses : **
- Conversant in French and in English (if not fluent) - Experience with NoSQL is a serious plus - Knowledge of P2P protocols (Hypercore, IPFS, SSB…) is also a serious plus
- Knowledge of Eclipse-based modelling technologies (e.g. EMF, Sirius, Xtext) - Knowledge of automated model management (e.g. model transformation, code generation) technologies
- The project aims at easing the daily work life of scientist researchers so sensitivity to the academic lifestyle is also a plus.
** Perks and benefits: **
You will ... - Work closely with cross-functional interdisciplinary scientific research and engineering teams,
- Evolve in a stimulating goal-oriented environment - Have the possibility of working remotely part of the week - Be involved in meaningful technological decision making - Enjoy unlimited free coffee/tea
https://www.emploi.cea.fr/Pages/Offre/detailoffre.aspx?idOffre=23814&idOrigine=502&LCID=1036&offerReference=2022-23814
We are actively looking for an engineer in charge of operations for the LNE's Artificial Intelligence and Cybersecurity Evaluation department:
https://www.lne.fr/fr/offre-emploi/ingenieur-en-charge-operations-departement-evaluation-intelligence-artificielle-0
The successful candidate will join a fast-growing team specializing in the evaluation of AI systems and working in many fields (TAL, image processing, smart medical devices, autonomous mobility systems, agricultural robots, cobots, etc.).
I am at your disposal for any exchange on this offer.
Thank you in advance for your applications and your shares, see you soon!
Guillaume AVRIN, PhD Head of the Artificial Intelligence Evaluation Department Head of cybersecurity testing activities
Directorate of testing and certification
National Metrology and Testing Laboratory 29 avenue Roger Hennequin 78197 Trappes Cedex - lne.fr
Developing systems towards robust discourse parsing and its application
https://pagesperso.irit.fr/~Chloe.Braud/andiamo/
- Contract duration: 12 months (flexible)
- Starting date: December 2022 (flexible)
- Location: IRIT, Université P. Sabatier (Toulouse III)
- Remuneration: starting at 2,745 euros, gross salary, depending on experience
- Application deadline: the position will be open until fulfilled
- Send application by email to [email protected]
Application procedure: please send a CV and a short letter motivating your application by detailing the following elements:
- indicate your **skills in machine learning**, e.g. the type of tasks you already worked on, the type of algorithms, the libraries used. Please specify your experience with neural architectures and pre-trained language models.
- describe your interest and/or experience in natural language processing, i.e. the type of tasks you already tried to solve if any, or similar problems you worked on, or why you now want to work in NLP and why you think your experience in another domain could be relevant
- If you are interested but don’t have a phd, rather a master / engineer diploma and your CV fits the requirements, please send me an email with the same information as above
Incomplete application will not be considered.
The AnDiAMO project: Natural Language Processing (NLP) is a domain at the frontier of AI, computer science and linguistics, aiming at developing systems able to automatically analyze textual documents. Within NLP, discourse parsing is a crucial but challenging task: its goal is to produce structures describing the relationships (e.g. explanation, contrast...) between spans of text in full documents, allowing for making inference on their content.
Developing high-performing and robust discourse parsers could help to improve downstream applications such as automatic summarization or translation, question-answering, chat bots, e.g. [1,2,3]. However, current performance are still low, mainly due to the lack of annotated data (see e.g. [4] on monologues, [5] on dialogues, [6,7] for the multilingual setting).
In order to develop robust discourse parsers within the AnDiAMO project, we want to explore multi-objective settings, where the goal is ultimately to perform a discourse analysis, but relying on another related objective such as performing well on another task (e.g. morphological, syntactic or temporal analysis), or an application (e.g. sentiment analysis or argument mining). We will also explore the issues of cross-language and cross framework learning.
The position is funded by the ANR AnDiAMO project, for which an engineer has already been hired, master interns will also be recruited. Collaborations are planned with researchers in Toulouse, Grenoble, Nancy and Munich. The hired person will be part of the MELODI team at IRIT, participating in team and project meetings, and co-authoring articles.
Research plan: The recruited candidate will work on one or several of the following topics, depending on its interests:
- Data representation: Discourse processing requires information from various levels of linguistics analysis. For now, existing studies do not make it clear what kind of information is important and needed, and some potentially relevant sources of information are ignored. We plan to explore this issue within a multi-task learning setting, where a system has to jointly learn different tasks. We will experiment on classification tasks (discourse relation, segmentation) and on full discourse parsing.
- Transferring to new languages, domains and modalities: Developing systems that perform well on domains or languages that are different from those used at training time is crucial, especially if the adaptation can be done in an unsupervised way. It is especially important for discourse, since annotation is very hard and time-consuming. We plan to experiment with cross-lingual embeddings and to explore multi-task learning, but trying to understand how to integrate additional linguistic information with only little annotated data for auxiliary tasks. We also want to investigate dialogues, for which only a few discourse parsers exist, and better understand how it differs from monologues.
- Extrinsic evaluation: We will investigate a few downstream applications that could benefit from discourse information, as a way to give an extrinsic evaluation. We will explore pipeline systems, varying the way we encode the discourse information as input of our end system. We will also explore transfer learning strategies, either via multi-task learning or representation learning. We plan to start with cognitive impairment detection (e.g. schizophrenia, Alzheimer) and argument mining. More applications will be considered, depending on the interest of the recruited postdoc.
It will be possible to investigate other paths of research, such as few-shot or unsupervised learning, depending on the interest of the recruited candidate.
Profile - PhD degree in computer science or computational linguistics
- Good knowledge in Machine Learning is required
- Interest in language technology / NLP
- Good programming skills: preferably with Python, knowledge of PyTorch is a plus
The Institute of Molecular and Clinical Ophthalmology Basel (IOB) invites applications for a joint Research Associate or Postdoctoral Researcher position mentored by Rava Azeredo da Silveira, Botond Roska, and Guilherme Testa-Silva.
The position is focused on understanding neuronal coding and representations using large scale voltage imaging datasets. A successful candidate will have a strong background in mathematics, statistics, artificial intelligence, physics, computer science or engineering. Proficiency in image processing, signal processing, clustering, and classification as well as experience with data-driven engineering, numerical methods, and neuroscience topics are highly desirable. Equally desirable are the spirit of intellectual adventure and the thirst for discovery.
The IOB offers highly competitive conditions in a dynamic and international research community in Basel. IOB is an equal-opportunity employer with family-friendly work policies.
Application / Contact Interested candidates should submit their application documents as a single PDF file to [email protected] including (1) a letter of motivation, (2) a statement of research interests, limited to two pages and (3) a curriculum vitæ including a list of publications. In addition, three letters of recommendations should be sent to the same email address.
For further information, please visit our website www.iob.ch or contact Rava A. da Silveira ([email protected]) or Guilherme Testa-Silva ([email protected])
The lab of Rava Azeredo da Silveira invites applications for Doctoral Student positions at IOB, University of Basel. Research questions will be chosen from a range of topics in theoretical/computational neuroscience and cognitive science, involving either data analysis or theory, and drawing on recent machine learning approaches.
Candidates with backgrounds in mathematics, statistics, artificial intelligence, physics, computer science, engineering, biology, and psychology are welcome. Experience with data analysis and proficiency with numerical methods, in addition to familiarity with neuroscience topics and mathematical and statistical methods, are desirable. Equally desirable are a spirit of intellectual adventure, eagerness, and drive.
The positions will come with highly competitive work conditions and salaries. For details, see https://www.silveira-lab.com/openings.
Application deadline: For full consideration, please apply by 15 November 2020.
How to apply: Please send the following information in one single PDF, to [email protected]:
1. letter of motivation;
2. statement of research interests, limited to two pages;
3. curriculum vitæ.
In all email correspondence, please include the mention “APPLICATION-PHD” in the subject header, otherwise the application will not be considered. Please also arrange for three letters of recommendations to be sent to the same email address.
The lab of Rava Azeredo da Silveira invites applications for Postdoctoral Researcher positions at IOB, University of Basel. Research questions will be chosen from a range of topics in theoretical/computational neuroscience and cognitive science, involving either data analysis or theory, and drawing on recent machine learning approaches.
Candidates with backgrounds in mathematics, statistics, artificial intelligence, physics, computer science, engineering, biology, and psychology are welcome. Experience with data analysis and proficiency with numerical methods, in addition to familiarity with neuroscience topics and mathematical and statistical methods, are desirable. Equally desirable are a spirit of intellectual adventure, eagerness, and drive.
The positions will come with highly competitive work conditions and salaries. For details, see https://www.silveira-lab.com/openings.
Application deadline: For full consideration, please apply by 15 November 2020.
How to apply: Please send the following information in one single PDF, to [email protected]:
1. letter of motivation;
2. statement of research interests, limited to two pages;
3. curriculum vitæ including a list of publications;
4. any relevant publications that you wish to showcase.
In all email correspondence, please include the mention “APPLICATION-POSTDOC” in the subject header, otherwise the application will not be considered. Please also arrange for three letters of recommendations to be sent to the same email address.
Six fully funded PhD candidate or predoc research positions on "Machine Learning and Computer Vision" and the "International Artificial Intelligence Doctoral Academy (AIDA)" in AIIA Lab, Aristotle University of Thessaloniki, Greece.
The Artificial Intelligence and Information Analysis Laboratory (AIIA Lab, AIIA.CVML R&D group) of the School of Informatics, Aristotle University of Thessaloniki, Greece (AUTH) has six open PhD candidate or predoc research positions. Applicants may become PhD candidates or just do R&D work. The interested applicant must have strong theoretical and/or applied background in machine learning and computer vision, with an emphasis on deep learning. Potential (not exclusive) application domains include robotics/autonomous systems and digital media.
Research topics: Extreme visual and social media data analytics for natural disasters (TEMA) Visual drone-based industrial pipeline inspection (SIMAR) Deep digital media analysis (AI4Media)
New decentralized deep learning methods (AI4Media) Fast embedded drone visual analysis (TEMA, AerialCore) Support International Artificial Intelligence Doctoral Academy (AIDA, AI4Europe)
The director of the AIIA Lab is Prof. Ioannis Pitas, who is also the chair of the International Artificial Intelligence Doctoral Academy (AIDA, from the AI4Media project). Thessaloniki is a large port city with very low living costs and easy access to many local tourist attractions, while AUTH is the largest university in SE Europe.
Links: International Artificial Intelligence Doctoral Academy (AIDA) AI4Media EU/Horizon 2020 Project (2019-2023)
Horizon Europe projects that just started or are expected to start soon: TEMA Horizon 2022 Project (2022-2026) AI4Europe Horizon 2022 Project (2022-2025) SIMAR Horizon 2022 Project (2022-2025)
What we offer - Competitive EU-level remuneration package and guaranteed funding for a minimum of 24 months, which can be extended to cover the entire PhD duration.
- Opportunities to develop research and programming skills and mentor M.Sc. students.
- International collaborations with many top universities/research centers/industries.
Candidate profile MSc degree (or any 4-5 year degree) in Computer Science or Electrical/Computer Engineering.
Good programming (C++, Python) and theoretical/math skills. Specialization or coursework in machine learning and/or computer vision are desirable.
Any publications in international journals or conferences are desirable. Good English writing skills. * Applications of persons who are expected to finish their studies in the very near future are welcomed.
Application The interested candidate must send an e-mail to Prof. Ioannis Pitas [email protected], until 11/11/2022, with the following attachments:
- Curriculum vitae,
- Publication list (if any)
Names of person to provide recommendation letters are welcomed.
Three fully funded postdoctoral research positions on "Machine Learning and Computer Vision" and the "International Artificial Intelligence Doctoral Academy (AIDA)" in AIIA Lab, Aristotle University of Thessaloniki, Greece.
Three fully funded postdoctoral research positions on "Machine Learning and Computer Vision" and the “International Artificial Intelligence Doctoral Academy (AIDA)” in AIIA Lab, Aristotle University of Thessaloniki, Greece.
The Artificial Intelligence and Information Analysis Laboratory (AIIA Lab, AIIA.CVML R&D group) of the School of Informatics, Aristotle University of Thessaloniki, Greece (AUTH) has three open postdoctoral research positions. The interested applicant must have strong theoretical and/or applied background in machine learning and computer vision, with an emphasis on deep learning. Potential (not exclusive) application domains include robotics/autonomous systems and digital media.
Research topics: Extreme visual and social media data analytics for natural disasters (TEMA) Visual drone-based industrial pipeline inspection (SIMAR) Deep digital media analysis (AI4Media)
New decentralized deep learning methods (AI4Media) Fast embedded drone visual analysis (TEMA, AerialCore) Support International Artificial Intelligence Doctoral Academy (AIDA, AI4Europe)
The director of the AIIA Lab is Prof. Ioannis Pitas, who is also the chair of the International Artificial Intelligence Doctoral Academy (AIDA, from the AI4Media project). Thessaloniki is a large port city with very low living costs and easy access to many local tourist attractions, while AUTH is the largest university in SE Europe.
Links: International Artificial Intelligence Doctoral Academy (AIDA) AI4Media EU/Horizon 2020 Project (2019-2023)
Horizon Europe projects that just started or are expected to start soon:
TEMA Horizon 2022 Project (2022-2026)
AI4Europe Horizon 2022 Project (2022-2025)
SIMAR Horizon 2022 Project (2022-2025)
What we offer - Competitive EU-level remuneration package and guaranteed funding for a minimum of 24 months.
- Opportunities to develop skills and mentor M.Sc./Ph.D. students.
- International collaborations with many top universities/research centers/industries.
Candidate profile 1) PhD degree* in machine learning and/or computer vision.
2) Strong publication record in well-known international journals and conferences.
3) Previous professional experience with international collaborative research projects (e.g., Horizon 2020/Horizon Europe) is desirable.
4) Good English writing skills.
* Applicants who are expected to defend their dissertation in the very near future are welcomed.
Application The interested candidate must send an e-mail to Prof. Ioannis Pitas [email protected], until 11/11/2022, with the following attachments:
- Curriculum vitae,
- Publications list
Names of person to provide recommendation letters are welcomed.
Ioannis Pitas [email protected]
https://scholar.google.gr/citations?user=lWmGADwAAAAJ&hl=en
We are recruiting a Research Master in AI on expressive speech synthesis from text.
This work is part of the Theradia project funded by BPI-France, which aims to develop an expressive conversational agent for digital cognitive remediation devices.
The detailed topic is available via the following link - http://intra-old.gipsa-lab.grenoble-inp.fr/transfert/propositions/3_2022-10-19_sujet_M2_ExpressiveTTS.pdf.
Do not hesitate to distribute this offer widely.
Gérard Bailly - DR CNRS CNRS, Grenoble-Alps Univ. & INP Grenoble GIPSA-Lab / Speech & Cognition dpt - Co-chair of the MIAI "Collaborative Intelligent Systems"
11, mathematics street - 38402 St Martin d'Hères Office: B358 - Tel: (+33|0)476574711 - Skype: gerard_bailly
https://www.gipsa-lab.fr/~gerard.bailly/ https://www.researchgate.net/profile/Gerard_Bailly