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

Latest research in deep learning has led to impressive results on many computer vision tasks (object recognition and detection, image generation from text, etc.). An important part of the quality of these results comes from the use of huge parametric models (e.g. GPT-3 has 175 billion parameters) and the use of huge image databases (for example, LAYON 5B has more than 5 billion image/text pairs). The size of the models and datasets raises important questions about the computational resources that must be used to train and exploit these models, since only the major economic players can now have access to them. In addition, the consumption of computing power and memory of such technology has a strong environmental impact. It is therefore important to find new approaches that are more frugal and simpler to learn, but that maintain at least today's performances, in order to better respond to the challenges of tomorrow's AI.

Recent works (Rajbhandari et al 2022; Lewis et. al 2021; Fedus et al 2022) have shown the relevance of using mixture of expert (MoE) models (Jacobs et al 1991; Masoudnia et al 2014) to build efficient, more resource-efficient models. These approaches have been proposed in the context of language models. The thesis aims at generalizing these works to other modalities, such as images. We plan to build on MoE models introduced in the image domain, such as (Chen 2019; Wang 2019) and study the possible developments that the above-mentioned recent literature can bring.

During this thesis, we will be interested in building model whose architecture (e.g., their number of layers) could vary dynamically depending on the difficulty of the examples to be processed or on computation time constraints. Similar to the cascade techniques in Adaboost classifiers (Freund and Schapire 1997), this type of architecture could quickly classify most images and would deploy more resources for "difficult examples" or those close to the decision frontier. The study will focus on defining new network architectures that evolve with the examples processed and can adapt its energy cost to the difficulty of the task at hand.

Candidates must have an M.Sc. or engineering degree in a field related to computer science, electrical engineering, or applied mathematics, with strong programming skills (in particular with deep learning frameworks). Experience with image processing will be a plus. Candidates are expected to have abilities to write scientific reports and communicate research results at conferences in English.

The position is starting as soon as possible with a salary of 32kEuros gross, and will be located in Caen, France. Applications should include the following documents in electronic format : i) A short motivation letter stating why you are interested in this project, ii) A detailed CV describing your past research background related to the position, iii) The transcripts for master degrees. iv) The contact information for three references (do not include the reference letters with your applications, as we will only ask for the reference letters for short-listed candidates)

Please send your application package to [email protected] and [email protected] .

Ideally located in the heart of Normandy, two hours from Paris and just 10 minutes away from the beaches, Caen, William the Conqueror’s hometown, is a lively and dynamic city.

The University of Sheffield has a vacancy for a postdoc with expertise in computer vision and deep learning for an exciting knowledge transfer project with industry on visual misinformation detection.

For more details and to apply: https://www.jobs.ac.uk/job/CTN703/ktp-associate-ai-software-developer-for-visual-misinformation-detection

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]

The Department of Advanced Computing Sciences (DACS) at Maastricht University, the Netherlands, is looking for a PhD candidate in the field of Natural Language Processing and, more specifically, Neural Machine Translation.

https://www.academictransfer.com/en/317743/phd-candidate-in-neural-machine-translation/

The position is embedded in the Cognitive Systems group of the department, and the candidate will work with other PhD candidates, postdoctoral researchers, and senior researchers. The candidate will conduct research in Natural Language Processing and will contribute to the development of a flexible multilingual machine translation model. The model will be adjustable to different settings and contexts (e.g. virtual assistants, online conferencing) making use of contextual information and transfer learning, in eXtended Reality (XR) environments. The position is supported by a large-scale, multi-disciplinary Horizon Europe project, which brings together universities, companies, and end-users, all active in the fields of AI and XR, aiming at designing novel human-to-human and human-to-machine interactions within XR. Maastricht University, being the Scientific Coordinator of the project, is playing a key role in it.

The tasks of the successful candidate include:

Research in machine translation and related interaction context, making use of the latest advanced in deep learning (e.g. transfer learning and zero-shot machine translation) and data science.

Publishing in top-tier journals and conferences.

Support in the integration of the produced models in eXtended Reality interfaces.

Participation in project meetings and contribution to reports, as well as possible travels across Europe and beyond for the implementation of the project and participation in conferences.

Assistance in teaching activities in the department.

A master’s degree (already completed or near completion) in NLP, deep learning, artificial intelligence, or a closely related field such as computer vision. Excellent programming skills (esp. Python) are required. Solid experience and interest in latest advances in AI, especially in the field of Deep Learning, with proven experience (e.g. through publications, prior projects, etc.).

Excellent command of English.

We are looking for a passionate and creative researcher, with serious interest in publishing in top venues in the field.

Team spirit is also very important, since a large team will work on the project, both within the department, as well as across other institutes in Europe.

Strong presentation, writing, communication and organization skills are required for this position.

Fixed-term contract: 4 years. The full-time position is offered for a duration of four years, with yearly evaluations. The salary will be set in PhD salary scale of the Collective Labour Agreement of the Dutch Universities (€2.541 gross per month in first year to €3.247 in the fourth and final year). On top of this, there is an 8% holiday and an 8.3% year-end allowance. You have to be willing to move to (the vicinity) of Maastricht. Non-Dutch applicants could be eligible for a favorable tax treatment (30% ruling). The terms of employment of Maastricht University are set out in the Collective Labour Agreement of Dutch Universities (CAO). Furthermore, local UM provisions also apply. For more information look at the website www.maastrichtuniversity.nl > About UM > Working at UM.

The preferred starting date is January 1st, 2023.

Maastricht University heavily invests in the growth of its STEM research and education. The Faculty of Science and Engineering – which houses the Department of Advanced Computing Sciences – is one of the focal points of these developments. Within the Faculty of Science and Engineering, over 260 researchers and more than 2,700 students work on themes such as data science and artificial intelligence, circularity and sustainability, and fundamental physics. https://www.maastrichtuniversity.nl/fse

The Department of Advanced Computing Sciences is Maastricht University’s largest and oldest department broadly covering the fields of artificial intelligence, data science, computer science, mathematics and robotics. Over 100 researchers work and study in the Department of Advanced Computing Sciences, whose roots trace back to 1987. The department’s staff teaches approximately 800 bachelor’s and master’s students in 3 specialized study programmes in Data Science and Artificial Intelligence. https://www.maastrichtuniversity.nl/dacs

Applicants are asked to send in their application by October 9, 2022. You may be invited for an interview via MS Teams or in person. To apply for the position, submit the following documents via Academic Transfer:

Cover letter (1 page max), which includes a motivation of your interest in the vacancy and an explanation of why you would fit well for the PhD position; A detailed CV;

A course list of your Masters and Bachelor programs (including grades);

Results of a recent English language test, or other evidence of your English language capabilities;

Name and contact information of two references preferably in a single PDF document, at the following link:

https://www.academictransfer.com/en/317743/phd-candidate-in-neural-machine-translation/

For informal questions, you can contact Stelios Asteriadis.

At the Information Engineering and Computer Science department of the University of Trento we are looking for an enthusiastic PostDoc to develop a core theory and set of algorithms for resilient AI-based self-programming.

Could you please forward the vacancy description below to anyone that comes to mind? Or please let me know if you'd like to know a bit more.

Thanks in advance,

Marco Roveri Email: [email protected]

Description: PostDoc position in Artificial Intelligence at the Department of Information Engineering and Computer Science of University of Trento to contribute to the development of a core theory and algorithms for resilient AI-based self-programming, i.e, to define mechanisms to enable agents to act in an informed and intelligent way in their environment, by changing autonomously the way they behave as a consequence of the information they acquire from the external world and exchange with the humans operating therein. The study will focus on extending existing approaches to AI Planning and LTL/LTLf synthesis by i) enriching the computed strategies with fault-tolerant capabilities, ii) considering several models at synthesis and execution time leveraging the most appropriate model depending on the observed contingency at execution time; iii) integrating reinforcement and model learning to enable for determining tolerant strategies that work in a reference model plus variations. The theoretical framework is complemented by the realization of prototype supporting tools as well as practical applications in selected realistic scenarios (e.g. manufacturing, intra-logistics, hospital, pharmaceutical).

Gross amount for Research Fellowship:Euro 30.200,00 / year

The call is now open.

Interested candidates shall contact Prof. Marco Roveri [email protected] to ask for additional information.

The Department of Information Engineering and Computer Science at University of Trento

The Department of Information Engineering and Computer Science - DISI (https://www.disi.unitn.it) primarily covers the topics of information technology and engineering and ranked first among computer science departments in Italy and 78th worldwide according to the latest U.S. News Best Global Universities ranking.

The University of Trento is one of the best universities in Italy, and the region of Trentino Alto Adige is a top location in Europe in terms of quality of life and efficiency of services.

The application must be completed and submitted by Octobre 31, 2022, solely by the online system at the following page:

https://www.unitn.it/en/ateneo/bando/75361/department-disi-call-for-the-selections-for-the-awarding-of-no-1-research-fellowship-decree-no-17420

Deadline August 31, 2021 04.00 PM CEST

Read carefully the announcement, the requirements and to include all the required documents. An application without the required information will be discarded without evaluation.

*Starting date:* Flexible.

*Application deadline:* Running until the position is filled.

*Salary:* 2 240 € gross/month (social security included)

*Mission:* research oriented (teaching possible but not mandatory)

*Keywords:* natural and spoken language processing, self-supervised learning, deep learning efficiency

** 1. CONTEXT* The ANR project E-SSL (Efficient Self-Supervised Learning for Inclusive and Innovative Speech Technologies) will start on November 1st 2022. Self-supervised learning (SSL) has recently emerged as one of the most promising artificial intelligence (AI) methods as it becomes now feasible to take advantage of the colossal amounts of existing unlabeled data to significantly improve the performances of various speech processing tasks.

** 2. PHD OBJECTIVES* This PhD program aims at providing efficient deep neural network architectures training to approach SSL with the speech modality while keeping model deployment in mind, e.g. some use-cases may require streaming capabilities. In this extent, this objective is decoupled in two axes with a gradually increasing difficulty.

First, the PhD candidate will leverage the existing and large literature from deep architecture efficiency to quickly, yet systematically, document the effects of carefully selected architecture alterations with the latest SSL architectures for speech. Second, the candidate will develop novel deep architectures with respect to different efficiency parameters including local storage or compute capability. The impacts of the latter goals will consistently be evaluated both at training and deployment stages to cover the whole life-cycle of the model.

** 2.1 RESEARCH DIRECTIONS* The latest and best performing SSL models for speech rely on the transformers neural networks. Hence, the PhD candidate will start with replacing blocks transformers that have been identified as being particularly computation demanding with more efficient alternatives.

A vanilla implementation of the self-attention layer induces a quadratic scaling of the computation and memory complexities of the model with respect to the input sequence length.

This is particularly problematic for speech as typical training utterances vary a lot in the time domain. To tackle this phenomenon, two directions can be followed:

1. Reduce the time-dependency of the scoring part of the self-attention layer.

2. Reduce the floating point operation complexity of the self-attention layer.

The former concept will be implemented by drawing inspirations from Luna [3]. Hence, the candidate will integrate existing or novel modules into the selfattention layer that decouple the inner query and key products from the time dimension reducing it to a fixed and controllable dimension. The second axis will be evaluated following low-rank decomposition of the self-attention cell methods like used in the Linformer [5], or entire novel attention cells like adopted in FNet [1], that are built with linear complexity in mind.

The candidate will also investigate alternatives to the transformers architecture. Indeed, and according to a recent trend in the literature, transformers seem to not be all we need. Not only self-attention layers are more computationally demanding than, for instance, convolutional layers, but they may also achieve degraded performance.

For instance, mixing tokens based on the Fourier transform [1], mixing linear layers [4] or convolutional layers [2] defeated transformers with much lower computational and memory burdens: MLP-Mixer [4] has a five times higher images-per-second throughput than the closest transformer. We hypothesize that there is no reason for the speech SSL community to stick with highly inefficient transformers. Thus, the candidate will carefully design both novel convolutional and mixing SSL models leveraging recent advances like EfficientNetV2 and MLP-Mixer [4].

- Master 2 in Speech Processing, Natural Language Processing, Computer Science or Data Science.

- Good mastering of Python programming and deep learning frameworks. - Previous experience in Self-Supervised Learning, acoustic modeling or ASR would be a plus.

- Very good communication skills in English. - Knowledge of French would be a plus but is not mandatory.

The thesis will be conducted within the Speech and Language Group (SLG) of the the LIA laboratory and the Getalp team of the LIG laboratory. The GETALP team and the LIA have a strong expertise and track record in Natural and Spoken Language Processing. The recruited person will be welcomed within the teams which offer a stimulating, multinational and pleasant working environment. The means to carry out the PhD will be provided both in terms of missions in France and abroad and in terms of equipment. The candidate will have access to the GPU cluster of both laboratories. Furthermore, access to the National supercomputer Jean-Zay will enable to run large scale experiments. The PhD position will be co-supervised by Prof. Yannick Est`eve (LIA, Avignon) and Dr. Marco Dinarelli (LIG, Université Grenoble Alpes). Joint meetings are planned on a regular basis and the student is expected to spend time in both places. Moreover, the PhD student will collaborate with several team members involved in the project in particular the two other PhD candidates from the E-SSL project, and the partners from LIA, LIG and Dauphine Université PSL, Paris. Finally, the project will involve Dr. Titouan Parcollet, co-creator of SpeechBrain, with whom the candidate will interact closely.

Applications must contain: CV + letter/message of motivation + master notes + possibly one or more recommendation letters (not mandatory, but it is a plus); and must be addressed to (all recipients): Titouan Parcollet ([email protected]), Yannick Estève ([email protected]) and Marco Dinarelli ([email protected]).

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

*Application deadline: 27 October, 2022*

Within the context of the eCREAM and of the IDEA4RC projects, funded by the European Union, we are inviting applications for two research positions on the subject of information extraction in the clinical domain in a multilingual perspective.

FBK is looking for candidates to cover 2 positions with dynamic, highly motivated, researchers in the field of “Natural Language Processing” for the NLP Unit of the Digital Health and Wellbeing (dHWB) Center.

The candidates will be asked to advance state-of-the-art research in the field of NLP, with particular emphasis on the development of techniques for information extraction in the clinical domain. On the topics above, the candidates will have the possibility to supervise PhD students and develop their own specific research directions in accordance with the strategies of the Research Unit and the dHWB Center.

The candidates will work in collaboration with other researchers of the NLP Unit and of the dHWB Center, as well as with the partners involved in EU projects. The candidate is also expected to contribute to proposals for funded activities, including reporting and dissemination of results (in both academic and popular venues). Furthermore, we expect the successful candidates to contribute to maintain a strong role of FBK in the Italian and international NLP community.

The purpose of the current call is an opportunity of working into an internationally renewed NLP group and develop their own research path in accordance with the long term strategy of the NLP Unit and the dHWB Center.

*Job requirements* *The ideal candidates should have:*

- PhD Degree in areas related to Computer Science or Computational Linguistics; - Research Expertise in Information Extraction; - Publication track record in the field of NLP; - Good Knowledge in application of deep learning techniques in NLP; - Strong programming skills;

- Good knowledge and proficiency of the English language; - Team working attitude; - Good communication and relational skills; - Autonomy in developing research and organising work activities;

*Additional requirements:* - Experience in supervision of internship and thesis of bachelor and master level on topics related to NLP; - Experience in working for international research projects;

FBK actively seeks diversity and inclusion in the workplace and is also committed in promoting gender equality.

*Employment* *Type of contract*: fixed term contract – full time *Start date*: preferably from November 2022

*End date*: 31 August, 2027 (eCREAM) / 31 August, 2026 (IDEA4RC)

*Gross annual salary*: about € 39.500

*Workplace*: Povo - Trento (Italy)

Interested candidates are requested to submit their application by completing the online form (https://jobs.fbk.eu/). Please make sure that your application contains the following attachments (in pdf format):

- Detailed CV including list of scientific publications - Motivation letter - Email address contact for two referees

*Application deadline: 27 October, 2022*

FBK is a private research institution devoted to excellence in research in numerous disciplines and designated to the role of keeping the Autonomous Province of Trento in the mainstream of European and international research. Each research area is assigned to a specific research center, of which there are eleven totals. Information regarding the research centers, their activities and production is available at http://www.fbk.eu/research-centers.

The Digital Health and Wellbeing (dHWB) Center (https://www.fbk.eu/it/digital-healthwellbeing/) focuses on supporting an equitable and sustainable public healthcare system based on the pervasive use of digital technologies and AI by both empowered citizens and healthcare professionals, in the context of the 4P medicine. The activities of the dHWB Center focus on promoting and supporting a value-chain that combines high-quality scientific research (open and targeted) and innovation (social and technological) to have a significant impact on society (citizens and healthcare system) and market.

The Natural Language Processing (NLP) research unit (https://ict.fbk.eu/units/nlp/) develops computational models of human languages, focusing on written texts. We are active in the following areas: *text mining (*document classification, information extraction and ontology population from text, semantic inferences, analysis of the sentiment and of the emotional content of texts); *conversational agents (*task oriented dialogue systems, collaborative human-machine dialogues, generation of explanations); and development of *linguistic resources*, particularly for the Italian language. In all the above areas, deep learning techniques are exploited. A common issue concerns the “explainability” of the choices carried out by the systems. We are fond of contributing to the Italian NLP community.

Research contract within the VITAL project (City, Temporalities, Language)

Labex The past in the present Session 2022/2023

The past in the present labex is recruiting a beneficiary postdoctoral researcher starting January 2, 2023 and for 8 months in the as part of a postdoctoral contract assigned to the VITAL project.

*Key terms:* urban planning, architecture, NLP, spatial dynamics, urban project, urban change, discourse of city specialists

The VITAL project (Cities, Temporalities, Language) associates in a way original and innovative researchers in natural language processing (TAL), architects and urban planners, in a research project partnership with the National Archives and in collaboration with other institutions. This project aims to understand how speeches and architectural and urban projects address space as a dynamic and to study how this dynamic is expressed.

The interdisciplinary approach adopted here mobilizes the treatment automatic languages ​​(TAL) in order to identify and analyze elements of discourse reflecting the notion of urban dynamics and its perception by specialists in the field of urban planning in planning projects and initiatives. This is to test the feasibility and reliability of an automatic linguistic analysis of expressions referring to the dynamics in the field of urban planning as well as to propose a modeling of the phenomena sought and a typology of markers characterized by associated properties.

- modeling of the information sought; - development of a tool for the automatic detection of this information ; - extraction and visualization of annotated information.

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.

- *Deadline for submitting applications: November 14, 2022 at noon* (Paris time) - Selection of applications: between November 16 and November 30 2022

- Announcement of results: December 1, 2022 - Starting date: January 2, 2023

Detailed job description and application procedures on the website of the

http://passes-present.eu/fr/appel-candidatures-contrat-de-recherche-projet-vital-ville-temporalites-langage-44610

UMR DIADE IRD is looking for an application development engineer to work on a biodiversity study and preservation project ( http://www.couvreurlab.org/erc-global.html )

The main activities will be to contribute to the development of the Web platform for data management and visualization; Set up data flow management; Design, develop the database and automate the import of data...

More details on the online offer: https://www.ird.fr/ingenieur-en-developpement-dapplications-hf

To apply, send your CV and cover letter to [email protected] before October 30, 2022.

https://railenium.eu/poste/22-40-doctorant-interoperabilite-semantique-des-processus-de-modelisation-de-systemes-ferroviaires/

Thesis title: Semantic interoperability of railway system modeling processes

Host laboratory: LIB - EA 7534, 9 avenue Alain Savary, 21000 Dijon, FRANCE - https://lib.u-bourgogne.fr/

Specialization of the prepared doctorate: Computer science

Position status: 36-month fixed-term contract Working time: Full

Planned start date: As soon as possible

Teleworking: partial possible (3d/week)

Required profile: Graduate of a university master's degree or engineering degree, you wish to pursue a doctorate in the railway environment.

You have knowledge of knowledge engineering (semantic web, ontologies) and model-driven system engineering (MBSE).

Programming skills are appreciated.

Knowledge of the railway sector and data processing is a real plus. You have a genuine interest in research and scientific production, You are curious and have a sense of initiative.

A good level in English (read and written) is required.

Job experience: Minimum 1 year

Location: Position based in Villeneuve d'Ascq.

To apply, send your CV and cover letter by e-mail to [email protected]

Do not hesitate to distribute this offer on your various networks.

Thanking you in advance, I wish you a good day!

Keywords: multi-agent simulation, mobility, traffic

Laboratory and research team IRIT (Toulouse Computer Science Research Institute, UMR 5505), Collective Intelligence and Interaction department, Multi-Agent Cooperative Systems team (SMAC) .

Scientific background As part of several research projects related to different aspects of mobility, which can range from the simulation of prospective scenarios of public transport policies, to the establishment of interactive environments for urban development related to transport, including aspects more oriented towards operational research problems related to transport, we are working on the development of a tool built on the GAMA simulation platform and allowing the simulation of multi-modal mobility dynamics on the scale of a metropolis. As part of this implementation, several missions are identified.

Missions identified We aim to set up a framework dedicated to mobility. Among the missions identified to date: Implement and maintain a set of traffic simulation models at different scales within the GAMA simulation platform.

Manage all the corresponding data upstream (demographic statistics, EMD, GIS) on different cities and participate in the development of tools allowing the exploitation of simulation results.

Design and develop interactive environments to study the impact of urban development on mobility.

Required profile Qualification required: master/engineer or doctor in computer science. Technical skills: experience in multi-agent modeling and development of multi-agent models (GAMA, Netlogo, …) good knowledge of data analysis, descriptive statistics

good knowledge of issues related to the processing of simulation results (exploration, calibration, validation) knowledge and practice of a scientific workflow would be a plus

Relational: The candidate must be motivated, curious and proactive, while being well organized.

Administration The duration of the contracts and the salaries will be determined according to the missions chosen.

Sending applications Applications are expected before October 28, 2022 and must be submitted via the following form: https://forms.gle/j5tPksv1SuFQAmwVA

Your application should at least include: abstract cover letter Transcripts from the license

As one of the few selected Universities of Excellence in Germany, University of Bonn already has a strong focus on all aspects of Artificial Intelligence, with research in machine learning, semantic modeling, robotics, and computer vision all the way to neuroscience and ethical foundations. As part of our strategic push into AI, we are now inviting applications for up to four additional, excellently equipped,

*Full Professorships (W3) / Tenure-Track Professorships (W1 to W3) in Artificial Intelligence and Machine Learning* to be part of the *Lamarr Institute for Machine Learning and Artificial Intelligence*

which is currently being created based on our existing Competence Center Machine Learning Rhein-Ruhr ML2R. The Lamarr Institute will bring together all AI activities of University of Bonn and its partners with significant growth based on permanent institutional funding.

Applicants are expected to have demonstrated internationally outstanding research in one or more relevant subfields of Artificial Intelligence with a strong focus on Machine Learning, if possible related to one or more of the five major research areas of the Lamarr Institute: - Resource-Aware ML: Optimize algorithms for available resources and new architectures

- Trustworthy AI: Make AI ethical, reliable, understandable, and certifiable - Hybrid ML: Combine data and knowledge in ML algorithms

- Human-Centered Systems: Exploit human interaction contexts when learning from data

- Embodied AI: Build ML algorithms that work in physical and autonomous systems

Professorships will be appointed as tenured full professor (W3). Dual-career appointments are possible for suitable candidates.

W1 Positions will be appointed as Junior Professorships for an initial phase of three years and will be extended for three more years after a positive intermediate evaluation. After successful tenure evaluation, the position will turn into a permanently tenured full professorship (W3).

The successful applicants represent the area in research and teach in the English (Master level) and German languages (Bachelor level) within the programs of study in the different programs at the Institute of Computer Science of University of Bonn (German language skills not required up front). The start of a degree program in AI is foreseen for the near future.

Besides integration into the Lamarr Institute, involvement with other major activities such as the excellence cluster PhenoRob and the transdisciplinary research areas of University of Bonn is possible. Close cooperation within our partner institutions is expected, as is the capability of positioning the Lamarr Institute towards society and industry. The acquisition of third-party research funds and participation in and contribution to joint grant activities in computer science are requested.

Formal requirements are defined by § 36 of the Higher Education Act of North RhineWestphalia (Hochschulgesetz Nordrhein-Westfalen). The University of Bonn actively supports diversity and equal opportunities. The University of Bonn has been certified as a family-friendly university and offers a dual career service. Its aim is to increase the proportion of women in those fields in which women are underrepresented and to place a special focus on promoting their careers. Therefore, the university specifically requests applications from suitably qualified women.

Applications will be handled in accordance with the Equal Opportunities Act of North Rhine-Westphalia. Applications from suitably qualified people with severe disabilities that have already been verified or from people with an equivalent status will be particularly welcomed.

Applications including the usual documents (Letter, curriculum vitae, list of publications, selected publications, research plan, teaching concept, copies of degree certificates) are expected in electronic form (one PDF file) until 12.12. 2022 addressed to the [email protected].

Further information about the position is also available from Prof. Dr. Stefan Wrobel (Bonn Director of the Lamarr Institute, [email protected]).

Lamarr Institute: https://lamarr-institute.org

W3 Professorships: https://www.uni-bonn.de/de/universitaet/medien-universitaet/medien-organisation-und-einrichtungen/medien-dezernat-3/w3-artificial-intelligence-machine-learning-engl.pdf

W1 with tenure track W3 Professorships: https://www.uni-bonn.de/de/universitaet/medien-universitaet/medien-organisation-und-einrichtungen/medien-dezernat-3/w1-articial-intelligence-machine-learning-tt-w3-engl.pdf

A Senior Researcher position is available at the Institute of Electronics and Computer Science (EDI), https://www.edi.lv/en, Riga, Latvia.

The position is open in the scope of the Horizon Europe project PRAESIIDIUM. The researcher is expected to take a leading role in the development of a next-generation wearable device.

Requirements include Ph.D. by start of the appointment, as well as enthusiasm and capabilities for applied research related to embedded systems, wearable computing, and signal processing.

This position is full time, with funding guaranteed for 3 years. Expected start date: January 1, 2023.

Application via email. Further details and contact information can be found at: https://euraxess.ec.europa.eu/jobs/841037

George Mason University is looking to recruit a postdoctoral fellow to support a transdisciplinary team of faculty on an ambitious project that brings together natural language processing (NLP), deep learning, and global policy to analyze, understand, and model AI infrastructure policy.

The project duration is April 15, 2022 to April 14, 2025. More information about it can be found at aistrategies.info

Qualifications of desired candidates include:

PhD in computer science or computational social sciences

Background in machine learning and deep learning

Experience with text mining and NLP is desired

Strong motivation to work on an interdisciplinary project

Strong interest in global policy issues related to AI infrastructures.

Interest in obtaining project management experience by managing a small team of researchers and graduate students

If interested, please contact: Amarda Shehu at amarda/AT/gmu.edu

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

Position: NLP Research Engineer (CDI)

Emvista transforms e-mail into a productivity tool thanks to Prevyo, an intelligent virtual assistant. Prevyo is able to redirect your e-mails, detect those that are really urgent, classify attachments, enrich your address book.

Emvista, a company located in Montpellier, is the publisher of Prevyo.

Prevyo is based on a hybrid artificial intelligence that combines the two machine learning/deep learning approaches and linguistic and ontological knowledge. This AI semantically analyzes e-mails based on many technological bricks such as the recognition of temporal expressions, the recognition of named entities or the extraction of events. This information is represented in an ontological form from which automatic reasoning is able to reveal knowledge that did not appear at first sight.

Reporting directly to the research director to strengthen the R&D team specializing in Natural Language Processing and Knowledge Representation technologies, we are looking for a research engineer in these areas.

You will also be in contact with the development team.

CDI Partial teleworking possible Montpellier

The main mission for the candidate is to take charge of work involving learning techniques and models (machine learning/deep learning) within Emvista projects. In this context, the missions are as follows:

Contribution to the research and development of technological bricks already existing at Emvista (parsing, normalization, recognition of named entities, analysis of opinions/emotions, automatic summary, extraction of keywords, generation of concepts, conversational agent, etc. )

Monitoring and state of the art in the field of NLP

Evaluation of NLP solutions (academic and industrial)

Supervision of students (trainees, doctoral students, etc. )

Scientific publications (articles in national and international conferences and journals, participation in workshops, etc. )

Popularization of research (journalistic articles, social networks, etc. )

More specifically, Emvista is the coordinator of a collaborative research project entitled POPCORN “Operational Population of Knowledge Bases and Neural Networks”. This project, subsidized by the Agency for Innovation and Defense (AID), involves three partners: Emvista, Airbus Defense and Space and the Grenoble Computer Science Laboratory (GETALP team). The POPCORN project addresses the problem of semi-automated enrichment of a knowledge base via automatic text analysis. The project focuses on the following three areas of research:

Generation of synthetic textual data from reference texts;

Recognition of entities of interest, associated attributes, and relationships between entities.

Semantic disambiguation of entities (in case of homonymy for example)

POPCORN will mobilize several people from Emvista's R&D team, including you, who will be tasked with taking charge of work involving machine learning/deep learning applied to text in collaboration with partners. The successful candidate will be fully invested in POPCORN during the first 3 years which correspond to the duration of the project, starting January 3, 2022. The results of the research carried out on the POPCORN project will be integrated into Emvista's marketed solutions, including Prevyo. This will include structuring the information contained in the e-mails (names of projects, activities, customers, etc.) in order to populate a database with a customer relationship management tool (CRM).

Profile & Attitude Very good knowledge of machine learning algorithms for automatic natural language processing

Mastery of recent language models, in particular for French (BERT, FlauBERT, CamemBERT, etc.)

PhD or engineering degree with specialization in Natural Language Processing

Mastery of research techniques and methodologies

Knowledge of new NLP technologies, statistical approaches applicable to NLP

Very good written expression in French (ideally in English as well)

To be a pedagogue

Good knowledge of Java, proficiency in Python as well as ML/DL frameworks (PyTorch, TensorFlow, Scikit-Learn...)

Host unit: Emvista (India Juliet group)

Location: Espace Bocaud, 42 rue de la Pierre Plantée, 34830 Jacou

Please send your application to [email protected] consisting of CV and cover letter.

As part of the R&D project Booster qaBot : Question Answering and Chatbot, bringing together the companies The QACompany, Wikit and the Hubert Curien laboratory, we are recruiting a post-doc or research engineer for a period of 18 months.

Conversational agents (chatbots) are increasingly used in all sectors to provide quick and cheap assistance to users. By asking a question, the user expresses his intention; this intention is recognized among a list of intentions of the system; the system then gives its answer to the user. Like any expert system, this technique has the advantage of providing precise answers because they are prepared. The disadvantage is that it requires a significant amount of time to design and maintain conversational scenarios with the associated intentions. Question Answering (QA) systems have appeared very recently, in particular to query document databases. The user sends his question, and the system answers by selecting a document and identifying the text answering the question. The technique of QA systems requires less specific design effort, but it currently requires very large training resources (questions and answers in documents) which limits its adoption beyond very large databases such as Wikipedia and for English.

The qaBot project focuses on automatic natural language processing (NLP) and deep learning. Its objective is to bring to the market a mixed approach combining Chatbot technology - provided by the Lyon-based company Wikit - and document-based Q&A technology - developed by The QA Company. The scientific and academic part of the program is under the direction of the Hubert Curien laboratory (with the University of Saint-Etienne and the CNRS as main supervisors).

The recruited person will have to invest mainly on the scientific support of the project on the aspects of the training of the models, for specific and small data (few shots regimes), the study and the synthesis of the recent works, and the implementation/evaluation of these. More specifically, the scientific challenges identified are

Designing a powerful neural architecture with few-shot training data sets for the task of extractive question answering on specific domains

Define metrics to evaluate the created chatbots. These metrics will be used to evaluate the systems during the project.

Rapidly adapt existing linguistic models to non-English languages.

Adapt the system to text corpora in specific formats (e.g. pdf or websites)

The candidate should have strong skills in Machine Learning (model design, mastery of deep learning frameworks such as PyTorch/TensorFlow), but also advanced skills in Python, a strong interest in textual data, question answering and so-called Large Language Models (BERT, PaLM), as well as overfitting and the application of the latter (in particular via HuggingFace)

The host site is the Hubert Curien laboratory, a joint research unit (UMR 5516) of the Jean Monnet University of Saint-Etienne, the Centre National de la Recherche Scientifique (CNRS) and the Institut d'Optique Graduate School. It is composed of about 90 researchers, professors and lecturers, 20 engineers and administrative staff and 130 PhD and post-doctoral students. Our research activities are organized into two scientific departments: Optics, Photonics and Surfaces and Computer Science, Security and Image. The Data Intelligence team, in which the person recruited will work, is specialized in the field of Machine Learning

The salary is flexible depending on the candidate's experience. The candidate will have access to a workstation with a computer allowing the use of the laboratory's computing cluster. The start of the contract is planned for the beginning of January 2023. The laboratory is located on the same campus as The QA Company, thus facilitating exchanges with the company's researchers and PhD student involved in the project.

To apply, please send to [email protected] and [email protected] : a detailed CV and a cover letter, as soon as possible.