ANNOUNCEMENT FOR ONE (1) POST-DOC AND (1) MASTER RESEARCH GRANTS IN THE SCOPE OF THE PROJECTS VISUAL-ID AND FACING2

APPLICATION opens from 27th of FEBRUARY till 24th of MARCH/2023 Ref.ª VISUALID_FACING-1 and -2: BI-BOLSA

Number of grants: 2 (1 POST-DOC + 1 MASTER) The Instituto de Sistemas e Robótica (ISR) – Universidade de Coimbra opens call for 1 (one) research grants (BI) for PhD holders and 1 (one) research Grant for MD holders. In the scope of the Scientific Research Projects – “VISUAL-ID” and “FACING2”, in cooperation with the Portuguese Mint and Official Printing Office (Imprensa Nacional-Casa da Moeda SA).

Scientific Area: Electrical and Computers Engineering, Computer Science, Biomedical Engineering, Informatics Engineering and affine areas.

Application profile: PhD in Electrical and Computers Engineering, Informatics Engineering, Computer Science, Mathematics, Biomedical Engineering, Physics Engineering or similar. The chosen applications will integrate a multi-disciplinary team with the objective of creating an authentication system of persons based on facial biometrics and the improvement of the authentication technology UniQode, using graphic codes, holograms and glitter inks, creating algorithms for security elements of printed and digital documents. The candidates must have skills in programming in C/C++ or python and experience with the library OpenCV. Knowledge in image processing, machine learning and in written and spoken English are valued.

NOTE: Candidates with foreign academic diplomas are obliged to present records of the equivalence/recognition of such diplomas and the conversion of the respective final notes to the Portuguese classification scale (whenever a final classification is attributed with the foreign diploma), issued by the Directorate-General for Higher Education or by a Portuguese public higher education establishment (regulated by Decree-Law no. 341/2007, of 12 October) or, in alternative, present the document of equivalence/recognition of such foreign qualifications to the corresponding Portuguese qualifications, issued by a Portuguese public higher education establishment (regulated by Decree-Law no. 283/83, of 21 June).

Project: These grants are supported by the VISUAL-ID and FACING2 projects.

Work plan: The selected candidates will develop tasks in the areas of image processing of faces (facial biometrics) and in the areas of facial recognition, liveness detection, verification of ICAO compliance of portraits, morphing attack detection, biometric template protection, among other areas. The tasks can include the development of modules for face image manipulation or of specific objects, programming convolutional neural networks for face recognition and mobile apps for the demonstration of the results of the project. This project results from the integration of the ISR-UC in the Innovation Network of the INCM and aims at manipulating of photos of faces for identity and travel security documents as the Citizen Card, Passports and others. The tasks include creating and developing computational tools for generating, reading and decoding machine-readable codes, namely the UniQode code, recently developed in collaboration with INCM, QRCode, DataMatrix, and other typically two-dimensional codes. It is intended to develop algorithms to standardize the creation, but especially with a focus on detection, rectification, reconstruction and decoding of them and oriented to mobile reading systems, such as the ubiquitous smartphones and tablets. The work plan will be adapted for the selected candidates in order to work in the development of high-end technologic products using research methods and algorithms in the area of recognition and machine learning.

Application submission: The applications shall be sent by email to [email protected], specifying in the subject: VISUALID_FACING-1. The application must include the following documentation: CV, habilitation certificate including the final scores obtained in the undergraduate subjects and a motivation letter. Recommendation letters are valued but not mandatory.

Submission of applications: The application process is open from 27th of FEBRUARY to 24th of MARCH of 2023.

More information in the following links: PhD: https://www.euraxess.pt/jobs/77142

Master: https://www.euraxess.pt/jobs/77119

Context --- Mass spectrometry is a technique to analyze chemical compounds by vaporizing molecules and measuring the quantities of ions that constitutes them at different mass/charge ratios. A mass spectrometer typically produces a high-dimensional vector (in the order of 1K to 10K components), called spectrum, that acts as a chemical signature of a sample. Mass spectrometry imaging (MSI) techniques can produce images of biological samples where each pixel is a high-dimensional spectrum; these images can be seen as maps of the molecular content of the samples, that can be used to localize specific structures like cancerous cells. Such images contain very rich data about the samples but are difficult to interpret by human operators. Machine learning-based techniques are typically used to help in their understanding, including deep learning models; however, these models face two major challenges:

- the high dimensionality of the spectra, - the limited amount of annotated data available to train them, which is difficult to obtain, especially in the fields of biology and medicine.

There is therefore a need for machine learning-based computer vision approaches that can classify high-dimensional samples in a weakly supervised setting or a few-shot learning setting.

This problem is addressed in the DEADPOOL project (In Vivo Ambient Water-Assisted Laser Desorption/Ionization Mass Spectrometry Imaging) funded by ANR (French national research agency) and run by PRISM (University of Lille / INSERM), CRIStAL (Univ. Lille / CNRS), and PhLAM (Univ. Lille / CNRS). The project aims at: - producing a high-definition MSI device that can be used in vivo, e.g. on patients in the operation theater, - developing computer vision techniques for the analysis of MSI images in near-real-time to map the content of the samples.

The application use case of the project is the semantic segmentation of MSI of tumors acquired in vivo, in the operation theater, as an assistive tool for surgeons. The project covers all aspects of the system, from its hardware and software design to its validation in clinical trials on dog patients.

Objectives

The objective of this post-doctoral position is to participate in the design of deep learning algorithms for the classification of high-dimensional data and with little annotated training data. The candidate will be expected to: - design new neural network models, training algorithms, or training workflows to tackle the classification of high-dimensional data with little annotated data, - validate the proposed models on standard datasets of the literature, - validate the proposed models on real-world MSI data from the project, - participate in the development of the prototype to be used in the clinical trial.

The scope of the contributions are not expected to be limited to the use case of the project.

The candidate will also participate in publishing the results of the project, producing deliverables, and attend project meetings.

Skills --- Candidates must hold a Ph.D. in computer science, signal and image processing, or a related field, with a specialization in machine learning or computer vision. Ph.D. students that expect to graduate by the starting date of the contract can apply.

Experience with one or more of the following items is a plus, but not mandatory: - deep neural networks, - weakly supervised learning, few-shot learning, or self-supervised learning, - semantic segmentation, - mass spectrometry data, - high-dimensional data (e.g. hyperspectral imaging).

The candidates must also have:

- good programming skills in Python and experience with machine learning libraries (pytorch, tensorflow/keras, scikit-learn, etc.), - good scientific writing skills, - scientific curiosity and the will to interact with researcher from other fields.

Knowledge of the French language is not mandatory.

Conditions

Contract duration: 23 months

Expected starting date: June 1st, 2023 (can be subject to negociation)

Salary: From 2350€/month to 2850€/month (gross salary) depending on experience, including health insurance, retirement fund, and 5 weeks/year of paid vacations.

Location: Our team is located in IRCICA, on the scientific campus of University of Lille in Villeneuve d'Ascq, France.

Equipment: The candidate will be provided a laptop computer for everyday tasks and given access to computing resources (GPUs), including hardware dedicated to the project only.

About CRIStAL, the FOX team, and Univ. Lille

CRIStAL is the laboratory in computer science, signal processing and automatic control of University of Lille. It gathers over 450 researchers in the field.

The FOX team is part of the Image research group of CRIStAL. We carry out research in computer vision, with a focus on (but not limited to) human behavior understanding. In recent years, we have developed machine learning-based techniques for data- and energy-efficient computer vision. We have a publication record in major venues in the field (IEEE TAFFC, IEEE TIP, Pattern recognition, IJCNN, WACV, etc.). We are also part of IRCICA, an interdisciplinary research institute of CNRS, where we conduct research on energy-efficient neural networks.

CRIStAL and IRCICA are located on the scientific campus of University of Lille, in Villeneuve d'Ascq (France). The campus is located near the city of Lille (15 minutes by car or subway). Lille is the largest city in Northern France. It can be easily accessed from Paris (1 hour by train), Bruxelles (30 minutes), and London (90 minutes), and is renowned for its cultural life, gastronomy, and friendly locals.

How to apply? --- Application process: Applicants should send

- a curriculum vitae,

- the contact info (name, position, email address) of (at least) two references,

- (optionally) recommendation letters, by email to Pierre Tirilly ([email protected]). Applications can be sent in English or in French. Shortlisted candidates will then be contacted for an online interview.

Timeline: Applications should be sent by 30 March 2023. Interviews will be programmed typically one to two weeks after reception of the application, and no later than April, 7th. Final decisions will be sent by April, 12th. This schedule may be extended if the position is not filled by April, 12th.

Contact --- Feel free to email Pierre Tirilly ([email protected]) for additional information about the position.

The INA (National Audiovisual Institute) ensures the legal deposit of television, radio and web media, and markets a large audiovisual collection to professionals.

The work carried out within the INA Research Department aims in particular to improve digital approaches for extracting, indexing, modeling, visualizing and understanding knowledge from the audiovisual collections kept by the institute. These digital methods are mainly used to help with the documentation of funds as well as in transdisciplinary works to have a better knowledge of the media and the way they speak about society.

In order to strengthen the work on the extraction of information from the text modality, the institute is recruiting a Researcher specialized in NLP (Automatic Language Processing) on a permanent contract. The priority topics he/she will be required to address are the semantic segmentation of audio streams (based on transcriptions) and the improvement of neural language models for final oral language comprehension (SLU) tasks. : classification, sentence labeling, vocabulary adaptation, …

Under the responsibility of the Head of Research, you will be in charge of:

Guarantee research missions in NLP (Automatic Language Processing) in particular the semantic segmentation of audio streams (based on transcriptions) and the improvement of neural language models for final tasks of oral language comprehension (SLU) : classification, sentence labeling, vocabulary adaptation, …

1 - Propose, design and implement complex and/or large-scale research and innovation projects

Define research projects related to this theme

Organize scientific monitoring and carry out research aimed at improving the state of the art, in particular on large corpora of data from INA collections

Design, implement, test, evaluate innovative technological tools within the framework of existing or anticipated uses of the Institute

Participate in the department's research and development strategy

Participate in the drafting of documents related to the activity (activity reports, project deliverables in particular).

2 - Coordinate the work of interns and doctoral students

3 - Create partnerships

4 - Propose and participate in collaborative research projects (regional, ANR, European funding, etc.)

5 - Collaborate with all the internal and external actors of the service, in particular the AI tribe within the DDT and the INA Lab (DDT/Heritage)

6 - Write or participate in the writing of scientific articles and present these articles in conferences, seminars or exhibitions

Diplomas Justify a doctorate in the field of computer science, specialty: automatic language processing and/or machine learning, or professional career recognized as equivalent.

LinkedIn job: https://www.linkedin.com/jobs/view/3499038776/

Position based in Bry sur Marne, partial teleworking possible

The first call for applications for SMASH postdoctoral Fellowships, co-funded by Marie Sklodowska Curie Actions, is now open. It offers excellent research opportunities that revolve around applications of machine learning, including deep learning in computer vision, to the fields of climate research, linguistics, precision medicine, and fundamental physics.

In this call, SMASH aims to hire 15 fellows who will be hosted in five Slovenian institutions. They can also spend up to 1/3 of their fellowship duration at one of our international academic partners (including top EU centres) or at some of the top Slovenian companies.

Each fellowship offers excellent working conditions, access to top infrastructure (including the peta supercomputer Vega), substantial research and travel funds, and a very generous salary that significantly exceeds local costs of living.

In order to apply, fellows need to contact their desired supervisor who will assist them in preparing short research proposals and provide them with the necessary letters of support from the host institutions.

For more information see: https://smash.ung.si/.

The application deadline is April 15th.

Prof. Danijel Skočaj [email protected]

Please share among PhD students and postdoc this call for a post-doctoral position on the detection of weak signals attack in an IoT Network. This position is joint between LabSTICC (Brest, FRANCE) and DISP lab (Lyon, FRANCE).

This project aims at analysing IoT network exchanges to identify security problems visible in the meta-data of the messages (infractions, inconsistencies…). For this, we integrate three dimensions. The first one, naturally, comes from business domain. The second is linked to the analysis of the IoT network’s properties. The third is the methodological aspects that allows to produce necessary software environment, considering constraints from the existing system and its possible evolutions.

Prerequisites: - Proficiency in French is not mandatory

- Good knowledge in some or all of the following: graph theory, artificial intelligence -- symbolic or data driven --, cybersecurity, software engineering

Job offer detail: - Duration is 24 month

- Salary is between 2000€ and 2200€

- Starts fall 2023

How to apply: Please send an email to [email protected] and [email protected] with your latest CV.

A Ph.D. scholarship is open for applications at University of Kent at Canterbury and University of Lille. The scholarship is available on a cotutelle (double award) basis: the Ph.D. candidate will spend part of their studies at University of Kent, and the other part at University of Lille.

The research topic is the development of energy-efficient training algorithms for spiking neural networks, applied to action recognition.

The scholarship includes a stipend for three years and tuition fees at the rate of UK students. International (non-UK) students are welcome to apply but will have to self-fund the difference between UK tuition fees and international tuition fees.

More detailed information about the position and the application process is available here: https://www.kent.ac.uk/scholarships/search/FNADNOVELN01.

The deadline for applications is 24 March 2023, 23:59 GMT.

Feel free to contact Dominique Chu ([email protected]) and Pierre Tirilly ([email protected]) for additional information.

The proposed PhD thesis will be developed in context of the ANR project entitled “Learning through epistemic reinforcement” (EpiRL) which was accepted in July 2022 and will be carried out between 2023 and 2027. The PhD thesis will start in September 2023 and will be funded on a three-year contract with gross salary of approximately 2000€ per month.

Description of the research project

The need for an integration of machine learning (ML) and knowledge representation (KR) has been largely emphasized in the artificial intelligence (AI) community. According to (Valiant, 2003), a key challenge for computer science is to come up with an integration of the two most fundamental phenomena of intelligence, namely, the ability to learn from experience and the ability to reason from what has been learned. The PhD thesis will be focused on the integration of epistemic reasoning and multi-agent learning. Different solutions of integration will be explored including:

· how to combine an agent’s capacity to attribute beliefs to other agents and to reason strategically with the capacity to form predictions about future events and future agents’ actions based on its past experiences;

· how to relate the notion of reward to mental attitudes including beliefs and desires;

· how to include in the description of a state used in an agent’s reward function the representation of other agents’ beliefs.

To this aim, we plan to combine concepts and methods from epistemic logic and planning (Fagin et al., 1995; Lorini, 2020; Davila et al., 2021), theories of learning in games and multi-agent learning (Fudenberg & Levine, 1998; Tuyls & Weiss, 2012), and the epistemic theory of convention (Lewis, 1969). We expect the kind of integration proposed in the context of PhD thesis to be relevant for AI applications in social robotics and human-machine interaction, given the importance of combining reasoning and learning as well as prediction and explanation for such applications.

Candidate profile

The PhD is at the intersection of logic, game theory and machine learning. The ideal candidate should have a strong mathematical background and a master’s degree in Logic, Computer Science or Mathematics. Ideally, it should be familiar with propositional logic, modal logic, epistemic and temporal logics, the theory of static and sequential games as well as with basic notions of machine learning.

PhD supervisor

The PhD supervisor is Emiliano Lorini, CNRS research director at the Institut de Recherche en Informatique de Toulouse (IRIT). See https://www.irit.fr/~Emiliano.Lorini/ for more information.

How to apply

Please email your detailed CV, a motivation letter, and transcripts of bachelor's degree and master’s degree to [email protected]. Samples of published research by the candidate and reference letters will be a plus.

APPLICATION DEADLINE FOR FULL CONSIDERATION: May 1st, 2023.

We invite applications for a 3-year PhD position at the University of Lille in the context of the recently funded research project "COMANCHE" (Computational Models of Lexical Meaning and Change). The position is funded by Inria, the French national research institute in Computer Science and Applied Mathematics.

COMANCHE proposes to transfer and adapt neural word embeddings algorithms to model the acquisition and evolution of word meaning, by comparing them with linguistic theories on language acquisition and language evolution.

At the intersection between Natural Language Processing, psycholinguistics and historical linguistics, this project intends to validate or revise some of these theories, while also developing computational models that are less data hungry and computationally intensive as they exploit new inductive biases inspired by these disciplines.

The first strand of the project, on which the successful candidate will work, focuses on the development of computational models of semantic memory and its acquisition. Two main research directions will be pursued. On the one hand, we will compare the structural properties associated to different semantic spaces derived from word embedding algorithms to those found in human semantic memory as reflected in behavioral data (such as typicality norms) as well as brain imaging data.

The latter data will then used as additional supervision to inject more hierarchical structure into the learned semantic spaces. One the other hand, we intend to experiment with training regimes for word embedding algorithms that are closer to those of humans when they acquire language, controlling the quantity as well as the linguistic complexity of the inputs fed to the learning algorithms through the use of longitudinal and child directed speech corpora (e.g., CHILDES, Colaje). In both cases, both English and French data will be considered.

The successful candidate holds a Master's degree in computational linguistics or computer science or cognitive science and has prior experience in word embedding models. Furthermore, the candidate will provide strong programming skills, expertise in machine learning approaches and is eager to work across languages.

The position is affiliated with the MAGNET team at Inria, Lille [1] as well as with the SCALAB group at University of Lille [2] in an effort to strenghten collaborations between these two groups, and ultimately foster cross-fertilizations between Natural Language Processing and Psycholinguistics.

Applications will be considered until the position is filled. However, you are encouraged to apply early as we shall start processing the applications as and when they are received.

Applications, written in English or French, should include a brief cover letter with research interests and vision, a CV (including your contact address, work experience, publications), and contact information for at least 2 referees. Applications (and questions) should be sent to Angèle Brunellière ([email protected]) and Pascal Denis ([email protected]).

The starting date of the position is 1 May 2023 or soon thereafter, for a total of 3 full years.

we have two postdoc offers in automatic recognition of speak at LISN (formerly LIMSI, Paris-Saclay University, CNRS) in Orsay.

- multilingual speech recognition: https://emploi.cnrs.fr/Offres/CDD/UMR9015-LUCOND-003/Default.aspx?lang=EN

- speech recognition in a constrained environment: https://emploi.cnrs.fr/Offres/CDD/UMR9015-LUCOND-002/Default.aspx?lang=EN

If you have a doctorate or have your planned defense soon and you are interested, you can contact us by

E-mail:

- Lucas Ondel Yang [email protected]

- Caio Corro [email protected]

We are both members of the TLP team. The department being being restructured, the announcements indicate the M3 team, which will be our future research team.

To apply for the offer, you must go through the CNRS portal (see links above).

BAG-ERA was born in 2016, founded by talented researchers in the aim of reconciling companies with their data. We edit and market software for aggregating, processing and enhancing the data from our customers.

Last year we embarked on a new project dedicated to the world of human resources: Emocio, a tool to help HR decision that will change everything 🚀.

Emocio uses annual performance interviews to detect important themes for each employee of large companies and analyze what impacts their opinion. We allow large companies to better understand what matters to their employees and their to prioritize HR actions.

The post 📣

The project started in 2022 and is already on the market. The number interviews analyzed is multiplied by 10 every 6 months. We have need to industrialize our processes, refine our algorithms and to add new features to our product.

We are looking for someone who can bring a linguistic perspective to the computer part. You will take the lead on the analysis part of text and improve the processing of interviews.

The challenge for us is to enable the product to scale up and this will be your guideline. For this, you will be assisted by 2 experts 👩🏻‍💻👨🏻‍💻 backend and algorithms for all things deployment and data management aspects.

Please note ⚠️ this is a research project (all solutions are not on the shelves) in business: it will therefore be necessary to juggle between long-term projects and short-term improvements.

Missions 👀

- Construction and management of annotation strategies (monitoring of annotated corpus, participation in the development of the tool annotation for experts, etc.)

- Development and improvement of classification algorithms multi-label (polarity, emotions, etc.)

- Analysis of the state of the art on detectable emotions at writing and product integration

- Participation in the product roadmap by integrating R&D topics

Depending on your profile and affinities, other missions may be entrusted (data-visualization, speech-to-text, etc.)/./

Required profile

Prerequisites

- 🎓 Doctoral degree in linguistics, automatic processing languages, machine learning or whatever suits you 🙂

- 🎯 An experience with the production of algorithms machine learning on a similar project

- Good level of French 🧀

- Good level of English 🍔

Further information

Contract 📄

- Type: CDI

- Start: ideally April 2023 and no later than September 2023

Conduct of interviews

- 1st interview to validate and detail the position

- 2nd interview to validate and answer the questions (and test technique 💪🏼)

Remuneration

- From 35k€ to 45k€ depending on profile, possible increase after the first year

- 100% mutual support (and a very good one too! 😉 @benefiz)

- Restaurant ticket card 💳

- Telework not geographically restricted 🌎 (I can work from anywhere)

What there is to know

- Offices in Grenoble in a tip top setting, among other startup, ETI and large groups

- Flexible hours

- Partial teleworking possible for the first 6 months, total possible after the trial period

- A diverse and dynamic team 😎, yes that's us! 😌

- To apply: https://bag-era.fr/job [email protected]

*Linguistic Resources and Technologies Project Manager**

*Inria Center **Nancy - Grand Est*

*City*: Nancy, France

*Desired start date:* 2023-04-03

*Type of contract: CDD 4 years*

*Level of diploma required: *BAC+5 or equivalent

*Desired level of experience:* 3 to 5 years

*To apply :* https://recrutement.inria.fr/public/classic/fr/offres/2023-05788

For more information, contact: [email protected]

*Full job description: * https://recrutement.inria.fr/public/classic/fr/offres/2023-05788

*CONTEXT*

This position is part of the Inria COLaF Challenge (Corpus and Tools for the Languages of France), which is a collaboration between the ALMAnaCH and MULTISPEECH teams. The objective of the Challenge is to develop and make language digital technologies available to the Francophonie and the languages of France, by contributing to the creation inclusive data corpora, models, and software bricks. The ALMAnaCH team focuses on the text and the MULTISPEECH team on multimodal speech. The two main objectives of this project are :

(1) The collection of French-speaking, massive and inclusive:* It is a question of constituting very large textual corpora and of speech, with rich metadata to improve the robustness of models in the face of linguistic variation, with a particular place for geographic-dialectal variation in the context of Francophonie, part of which may be multimodal (audio, image, video), or even specific to French sign language (LSF). THE data related to multimodal speech will concern among other things dialects, accents, speech of the elderly, of children and teenagers, LSF and the other languages widely spoken in France.

Corpus collection will be based primarily on data existing. These data (multimodal speech) can come from INA and regional or foreign radio and television archives, but rarely in a directly exploitable form, or with specialists, but in the form of small scattered corpora.

There difficulty consists on the one hand in identifying and pre-processing the data relevant in order to obtain homogeneous corpora, and on the other hand to clarify (and if possible relax) the legal constraints and the financial counterparties governing their use in order to ensure the impact as wide as possible. When legal constraints do not allow not to use existing data, an extra effort to data collection will be required. This will probably be the case for children (educational applications) and the elderly (health applications). Depending on the situation, this effort will be outsourced to field linguists or will lead to a campaign to large scale. This will be conducted in collaboration with Le VoiceLab and the DGLFLF.

(2) The development and availability of technologies inclusive linguistics: *Linguistic technologies considered in this project by the MULTISPEECH team are the recognition and speech synthesis, and sign language generation. Of many technologies are already on the market.

It is therefore a question of not reinvent these tools, but modify them necessary, so that they can exploit the inclusive corpora created. The technologies that will be used in this project relate to, including, but not limited to, the tasks following:

- Identification and (semi-)automatic pre-processing of data relevant within existing masses of data. This includes the detection and replacement of named entities for purposes of anonymization.

- Neural architectures and approaches adapted to the scenarios to be low resources (data augmentation, learning by transfer, weakly/unsupervised learning, learning active, and combination of these various forms of learning)

*ASKS*

The project engineer will have two main missions:

- Project management and practical coordination of the contribution of the MULTISPEECH team at the Inria Challenge. The project lead engineer will work in close collaboration with a “junior” engineer, a researcher and two doctoral students, all working within the framework of this project. He will provide close supervision of the engineer "junior" and very frequent interaction with the researcher and doctoral students. He will also be in contact with the members of the MULTISPEECH team. There will certainly be consultation and a solid collaboration with his counterpart within the team Almanac.

- Data collection and creation of multimodal speech corpus (this includes: certain dialects, accents, people elderly, children and adolescents, LSF and certain languages widely spoken in France other than French). A big part of the data collection will be done with associations of speakers, content producers and any relevant partners for data recovery. The project engineer will be brought to discuss, in particular the legal aspects, with our interlocutors.

*MAIN ACTIVITIES*

- Definition of the different types of corpus to be collected (identify the potentially exploitable corpora, establish a priority and a collection schedule)

- Collection of speech corpus from content producers or from any other partner. (ensure that the data respects the standards and quality standards)

- Negotiation of data usage contracts, ensuring respect the legal aspects (negotiate the conditions of use of data with content producers or partners, ensuring that the property rights intellectual property are respected and that the legal aspects are taken into account).

- Creation and provision of linguistic technologies for the processing of these corpuses: once collected, the data must be analyzed and processed in such a way as to extract useful information. The project engineer must propose technologies and tools among the existing ones, necessary for this analysis, and ensure that they are accessible to users. - Close supervision of the junior engineer: support and advice on the technical and strategic choices of development.

- Consultation and facilitation of exchanges between project members: (1) with the researcher and the two doctoral students (reflections and exchanges on the data, and their adequacy to the Challenge.); (2) coordination with project members within the ALMAnaCH team.

- Technological watch, in particular in the field of this challenge. - Writing and presentation of technical documentation

Note: This is an indicative list of activities that may be adapted in compliance with the mission as worded above.

*SKILLS*

REQUIRED PROFILE : - Graduate in computer science, linguistics or any other training in the field of automatic speech processing or LANGUAGES - Proven experience in project management and communication - In-depth knowledge of language technologies - Ability to work in a team and meet deadlines - Good knowledge of English

KNOWLEDGE - Ability to write, publish and present in French and in English - Mastery of project management and negotiation techniques - Legal bases (personal data, intellectual property, Business Law)

EXPERTISE - Analytical, writing and synthesis skills - Know how to accompany and advise - Know how to develop a relational network - Know how to lead different projects at the same time - Negotiation skills

KNOW-HOW - Sense of responsibility and autonomy - Sense of contact and taste for teamwork - Rigour, sense of priorities and reporting - Relational qualities (listening - diplomacy - power of conviction) - Appetite for negotiation (The VoiceLab, DGLFLF, etc.) - Ability to anticipate - Spirit of initiative and curiosity of mind

**FURTHER INFORMATION*

*Full-time position, to be filled as soon as possible. Remuneration according to experience. Applications must be submitted online on the Inria website. THE processing of applications submitted through other channels is not guaranteed.

*ABOUT INRIA*

Inria is the national science and technology research institute digital. World-class research, technological innovation and entrepreneurial risk are its DNA. Within 200 project-teams, mostly shared with major universities of research, more than 3,500 researchers and engineers are exploring new paths, often in interdisciplinarity and in collaboration with industrial partners to meet ambitious challenges. Inria supports the diversity of paths to innovation: from publishing open source software to building tech startups (Deep Tech).

*ABOUT THE INRIA NANCY – GRAND EAST CENTER*

The Inria Nancy – Grand-Est center is one of nine Inria centers bringing together 400 people, divided into 20 research teams, and 8 research support services. All these research teams are common with academic partners, and three of them are based in Strasbourg.

This research center is a major and recognized player in the field digital sciences. It is at the heart of a rich R&D ecosystem and of innovation: highly innovative SMEs, large groups, start-ups, incubators & accelerators, competitiveness clusters, players in the research and higher education, research institutes technological.

*WORKING ENVIRONMENT*

The project engineer will work within the project team MULTISPEECH at the Inria Nancy Research Center. The research of MULTISPEECH are centered on multimodal speech, in particular on its analysis and its generation in the context of the interaction man-machine. A central point of this work is the design machine learning models and techniques to extract information about linguistic content, identity and states of the speaker, and the speech environment, and to synthesize the multimodal speech using limited amounts of data labeled.

To apply - https://recrutement.inria.fr/public/classic/fr/offres/2023-05788

In the context of the upcoming interdisciplinary project 'impresso - Media Monitoring of the Past II' ('impresso doppio''), the EPFL Digital Humanities Laboratory is looking for one postdoctoral researcher and one research data engineer who will work with us on the design, development and evaluation of large-scale text mining pipelines for multilingual historical newspaper and radio archives.

=> NLP Research Data Engineer: https://go.epfl.ch/impresso-nlp-job1

=> NLP Postdoctoral Researcher: https://go.epfl.ch/impresso-nlp-job2

FOR BOTH POSITIONS: Application deadline: 21.04.2023.

Interviews: End of April.

Foreseen start of contract: 01.09.2023

Employment duration: 3.5 years (1-year contract renewable until the end of Feb 2027). Employment rate: 100%.

Salary: according to EPFL salary scales and experience.

Place of work: EPFL DHLAB, Lausanne, Switzerland. Contact: for any questions feel free to contact Maud Ehrmann (maud.ehrmann [at] epfl [dot] ch).

How to apply: please upload your application (full CV and cover letter) via the EPFL portal, cf. links above.

ABOUT THE PROJECT:

"impresso - Media Monitoring of the Past II" is an interdisciplinary research project which aims to pioneer new approaches to the joint exploration of newspaper and radio archive contents across time, languages, and national borders. Funded by the Swiss National Science Foundation and the Luxembourg National Research Fund (2023-2027), it is carried by the EPFL DHLAB (http://dhlab.epfl.ch/), the Department of Computational Linguistics (http://www.cl.uzh.ch/de.html) of the University of Zurich, the Centre for Contemporary and Digital History (C2DH, http://c2dh.uni.lu/) and the History Department (https://www.unil.ch/hist/fr/home.html) of the University of Lausanne, with the additional support of 21 European partners. Computational linguists, computer scientists, digital humanists, historians, and designers will work closely together to enrich and connect newspaper and radio sources through multiple layers of cutting-edge semantic enrichments represented in a shared multilingual vector space, and to design adequate, meaningful and transparent exploration capabilities for (data-driven) historical research in transnational and transmedia perspective. Impresso doppio (https://data.snf.ch/grants/grant/213585) follows on from the first impresso (https://impresso-project.ch/) project which developed a scalable architecture for the processing of Swiss and Luxembourgish newspaper collections and created an interface (https://impresso-project.ch/app) with powerful search, filter and discovery functionalities based on semantic enrichments. The present project puts forward the vision of a complete connection between media archives across languages and media types.

WE OFFER:

Opportunity to join an experienced and highly motivated interdisciplinary team conducting innovative and relevant research at the intersection of computer science and humanities research.

Applied research framework: what you will develop will be deployed in production and directly used by a community of researchers.

Work in an interdisciplinary team at the intersection of computer science, NLP, history, journalism and digital library.

Flexible working hours and teleworking.

Located in Lausanne, Switzerland, EPFL has a highly international environment, state-of-the-art research facilities, and is consistently ranked among the world's leading institutions in scientific research. Lausanne is a vibrant and cosmopolitan city centre in a unique natural environment with great outdoor activities (Jura, Alps, Lake Leman). Salaries and benefits are internationally competitive.

POSITION 1: NLP Research Data Engineer:

Apply online: https://go.epfl.ch/impresso-nlp-job1

Your mission:

The impresso project will compile an unprecedented transmedia and transnational corpus (historical newspaper and radio collections from 8 Western European countries) and develop a technical framework for its annotation, integration and exploitation. In this endeavour, you will lead the activities related to the management and engineering of the project data and system architecture. In collaboration with other project team members, you will contribute to the design and implementation of the technical framework.

Key responsibilities:

Design and implement scalable data pipelines to convert, cleanse, integrate and consolidate media archives. This includes defining appropriate data structures, models and formats for source documents and enrichments, as well as developing large-scale ingest workflows.

Establish a sustainable system architecture and pipeline management, including unit and integration testing.

Manage, document, and release code modules and datasets.

Actively collaborate with C2DH and UZH teams on data modelling, formats and APIs.

Engage in participative interface and API design with project team and partners.

Contribute to the organisation of annotation and evaluation campaigns (e.g. in the vein of HIPE (https://hipe-eval.github.io/).

Contribute to the organisation of project workshops on the development and adoption of standards for the representation and exchange of historical data (raw material and annotations).

Contribute to the definition of a roadmap towards the long-term maintenance and expansion of a rich ecosystem of tools, resources and services around historical media.

Participate in other impresso work packages where your expertise is required and coordinate with project team members and partners.

Initiate and/or contribute to scientific publications on data releases, processing and standards (and more topics if interested).

The work will be carried out in collaboration with the project team (ca. 12 people).

Your profile:

An experienced research data engineer (2-4 years) or NLP researcher/programmer with an interest in history, media and participatory design.

A degree in computer science, natural language processing or a related field (master or PhD), or equivalent professional experience.

Proficiency in: Python; Unix-based operating systems; database development and use (mysql and nosql); use of cloud storage and cloud computing (S3 object storage, Kubernetes); automation and scripting.

Good understanding of machine learning.

Willingness to write good documentation.

Good communication skills.

Strong collaborative and team spirit.

Autonomous and accountable with a proactive approach.

Efficient, committed to deadlines and concerned with production readiness.

Fluency in English.

Comfortable in an international and multi-cultural context.

Desirable

Experience working in a scientific and academic context.

Knowledge of French or German is a plus.

Interest in getting involved in supervising activities (MSc students).

Interest in writing scientific papers (on data and infrastructure-related topics, or more if interested).

POSITION 2: NLP Postdoctoral Researcher:

Apply online: https://go.epfl.ch/impresso-nlp-job2

Your mission:

You will conduct research in natural language processing and text mining on historical texts, with the aim of developing powerful information extraction methods on heterogeneous, multilingual and challenging radio transcripts and newspaper archives.

Key responsibilities:

Develop approaches to advanced named entity processing, quote extraction and segmentation and classification of media content.

Contribute to semantic indexing integration of media archives.

Contribute to the co-design of the interface and dedicated developments supporting the 4 historical use cases of the project.

Contribute to the organisation of international evaluation shared tasks on historical document processing.

Contribute to the organisation of project workshops on media mining, semantic indexing and processing pipelines.

Participate in other impresso work packages where your expertise is required and coordinate with project team members and partners.

Presentation of research results and participation in scientific and communication events.

Assistance with project management and organisational tasks.

Your profile:

PhD (obtained or close to completion) in natural language processing, machine learning, computer science or related areas.

Strong background in machine learning foundations and willingness to apply approaches to real and large-scale data.

Experience in deep learning, language models, information extraction.

Strong programming skills (Python, deep learning frameworks) and knowledge of Unix-based operating systems .

Curious, creative and highly motivated about scientific research and the application of NLP to digitised cultural heritage collections.

Very good communication, presentation, and writing skills in English.

Comfortable in an international and multi-cultural context.

Desirable

Understanding of image processing is a plus.

Experience of working with historical documents and in an interdisciplinary environment.

Knowledge of French or German is a plus.

Willingness to (co)-supervise student projects, internships and master theses.

In the context of the ANR DATAZERO 2 project (datazero.org), we are currently seeking applications for one PostDoc and one DevOps Engineer.

Duration: 12 months

Remuneration: depending on profile and experience, according to the University's salary scale.

Position to be filled as soon as possible. The applications will be evaluated as soon as they arrive.

Location: IRIT laboratory, Paul Sabatier University (Toulouse, in France)

Context : Following the ANR DATAZERO [1] project (2015-2019), this positions are placed in the context of the ANR Datazero2 (2020-2024). The DATAZERO2 project (a project of the French National Research Agency) in partnership with IRIT (Toulouse), LAPLACE (Toulouse), FEMTO St (Belfort-Besancon) and the industrial partner EATON (Grenoble), aims at improving the operation and design of datacenters operated with local renewable energy sources.

The position will be supervised by IRIT's SEPIA team. The SEPIA team has been working for several years on the optimization of the energy consumption of datacenters.

Postdoc research contribution: depending on the profile, experience and interest of the student, two research proposals could be studied:

(priority 1) working on the negotiation module. The idea of this module is to find a tradeoff between the power needed to run users tasks and the power available, under uncertainty conditions. Some leverages could be applied on IT applications (postponing, DVFS…) so that the energy budget of the execution could be changed. On the electrical part, storage capacities could also help fit the demand. Different solutions could be envisioned based on a multi-agents approach, game theory, or demand response. A solid work has already been published without considering uncertainty [2].

(priority 2) working on IT optimization. During the project, different optimization solutions have been studied by the team: offline IT scheduling under power constraints, online IT scheduling under power constraints. Uncertainties are also currently studied. In the context of this postdoc we would be interested in studying the integration of the datacenter to the city smart grid. An IT optimization could then be studied by considering the energetic mix at different times and trying to minimize the carbon footprint.

Skills, Expected abilities, one or more of the following

• Distributed systems

• Optimization, Multi-Agent System,

• Fog/Edge computing

Engineer Position: Devops

The recruited engineer will participate in the Datazero middleware continuous integration and deployment (CI/CD). The technologies used in the project are : C++/Java/Python,ActiveMQ, Protobuf, Gitlab, Docker, …

Final choice on the CI/CD framework is under way and the recruited engineer will contribute to the choice and to the final deployment.

Applications :

PostDoc : You can submit your application (CV/Cover Letter) to Georges Da Costa ([email protected]), Patricia Stolf ([email protected]) and Jean-Marc Pierson ([email protected])

Engineer : You can submit your application (CV/Cover Letter) to Amal Sayah ([email protected]), Patricia Stolf ([email protected]) and Jean-Marc Pierson ([email protected])