A call for 2 research engineer each of 9-months to develop models and simulation algorithms of the health state of a territory: a case study in monitoring pollen-mold concentrations in Normandy.

Summary : The project aims at developing models and algorithms for predicting and simulating the health state of a territory. The project consists of two steps. First, data of pollen-mold related to the health of a territory should be represented, analysed and modelled. Second, the practical interest of prediction and simulation are performed on the prepared data. The framework will then be used to simulate and predict the effect of a public decision (e.g. the requirement to wear masks).

The mission will be located at the GREYC Laboratory (University of Caen Normandy, CNRS UMR 6072), they will start both in January 2022.

Required scientific background: The candidate must have a Master degree or higher in Computer Science. Candidates with strong scientific skills in data science are recommended for one position, and on spatiotemporal representations and prediction/simulation for the other position.

Application: Candidate should send their CV and a motivation letter to [email protected] , and abdel-illah. [email protected].

Call for tenders for 2 contracts of 9 months research engineer to develop techniques for modeling and simulation of the state of health of a territory: application to the monitoring of pollen-mold in Normandy.

Summary: The project consists of representing, analyzing and modeling the state of health of a territory and its evolution over time from data from various open and non-open sources. Also, this project must make it possible to simulate actions to modify elements of the territory and consequently the state of health of the latter. For example, the effect of mandatory masks on the spread of a virus could be measured.

Both missions begin in January 2022 at the GREYC laboratory (University of Caen Normandy, CNRS UMR 6072).

Prerequisite: The candidate must hold a master's degree or an equivalent degree or higher in computer science. For the first contract, the candidate must have a solid knowledge of data science (data extraction and representation). For the secondcontract, the candidate must have skills in the representation of spatial/temporal information and in the fields of prediction and simulation.

Title: Automatic Analysis of the Captured Movement in a Learning Situation (AMOCA)

Keywords: Virtual reality, professional gesture learning, motion capture, machine learning

Supervisor (s) Ludovic HAMON ([email protected]), Sébastien George ([email protected])

Context of the internship. The internship focuses on the design and implementation of artificial intelligence tools making it possible to evaluate technical gestures (e.g. welding gestures, painting gestures, gesture of laboratory):

executed in a virtual environment

and obtained using any motion capture equipment.

The 6-month internship will take place face-to-face at CERIUM2 at the IUT de Laval. Telecommuting is possible part-time (2 days a week). The internship may continue as a thesis on automatic evaluation of dental surgery procedures (ANR EVAGO project, funding obtained). Subject of the internship: The democratization of motion capture tools made it possible to record and reproduce movements of the human body and manipulated objects for cinema, video games and virtual reality.

These movements are represented by time series made up of positions in 3D Cartesian space and orientations (Euler or quaternion angles) of body parts or objects handled.

In a learning situation where the professional gesture is an essential component (e.g. learn welding, first aid, painting, dental surgery), these new types of data bring a certain educational added value [1,2,4]. Indeed, record and observe these movements in a virtual environment, and automatically evaluating them allows in particular:

for the learner, to observe their performance, study their practices and compare them with expert gestures

for the teacher, to be able to manage the practical work of a larger number of students, to observe their performance a posteriori and to adapt its pedagogy accordingly. However, to achieve this objective, technical and scientific obstacles must be lifted and among them, this internship will focus on:

Signals of a heterogeneous nature: the diversity of motion capture tools (e.g. HTC Vive controllers and headphones, wiimote, combination of gyroscope accelerometers, https://www.vr-motion-learning.com/ etc ...) and as a consequence of the signals they produce in terms of frequencies and structure of data, is hampering the development of an analysis platform adaptable to any capture equipment.

Automatic evaluation of movement: a "good" gesture depends on the task to be learn, teaching practices and the business domain. Although it is possible to calculate kinematic (e.g. speed, acceleration), dynamic (i.e. applied force ...) or geometric patterns (e.g. the back should remain straight), determine which indicators will be relevant and their “threshold” values ​​making the gesture “acceptable” is a complex and tedious task, if performed manually.

This internship aims to contribute to the development of a new platform called PAMOCA for "Captured Motion Analysis Platform" according to two lines of work:

• Axis 1: Set up the technical tools allowing the application of pre-treatments (e.g. filter averaging, Savitzky-Golay filter, linear interpolation) and processing (i.e. calculation of indicators kinematics and geometry mainly) to any signal from any motion captures.

This will require the specification and implementation of a structure common data bridging the signals and the (pre-) processing to be applied. One of objectives of this axis will be to obtain data / signals conforming to specifications (e.g. frequency / sampling, noise).

• Axis 2: Use Artificial Intelligence (AI) tools to determine indicators and their threshold values ​​evaluating the technical gesture. Two approaches will be considered and compared:

one semi-supervised approach based on the use of recursive clustering techniques, in order to form groups of acceptable and unacceptable actions, according to preliminary indicators chosen (following the work of [2]) and

a supervised approach based on the use of forests random in order to define which indicators to choose and their value by exploration decision trees generated (continuation of the work of Noura Joudieh's internship over the period 2021 to LIUM).

This internship will further contribute to the ongoing bibliographic study on this subject [1,2,3,4].

The candidate's profile: Master 2 or an engineering degree in computer science. The candidate must:

• Have knowledge

o strong in machine learning (Python) and virtual reality

o in 3D modeling or geometry is a plus

• Work with c method and rigor and have organizational skills, interpersonal skills, listening and availability.

Applications are invited for a 24-month research position starting between January and August 2022, in the climate research group of the CNRM in Toulouse, France (http://www.umr-cnrm.fr/) to work on the parameterization of surface turbulent fluxes in polar regions using machine learning techniques.

Context: The Arctic sea ice has experienced a drastic decline over the last decades, perceived as an emblematic sign of climate change. Substantial reductions in sea ice cover, and also thickness, among other modifications, have already impacted largely on local ecosystems, indigenous populations and possibly lower-latitude climate. A further reduction in the sea ice cover and thus more open water exposed to the atmosphere is expected in the near future. Two to four times faster surface warming has also been observed in the Arctic than at any other latitude over the last decades. This phenomenon is commonly referred to as the Arctic amplification. Heat exchange between sea ice and atmosphere plays a crucial role on the rate of Arctic sea ice melting as well as on the teleconnections between polar and non-polar regions.

The Year of Polar Prediction (YOPP) was an extended period (2017-2019) of coordinated intensive observational and modeling activities aiming at improving polar prediction capabilities. YOPP is a WCRP/WWRP (World Climate Research Programme / World Weather Research Programme) initiative as part of the Polar Prediction Project. YOPP provided a wealth of new observations in the polar regions, that we can exploit to develop new parameterisations of the ice-atmosphere interface, in particular for latent and sensible heat fluxes.

Mission: This position is funded by the ‘Make Our Planet Great Again’ research program through the 5-year ASET project (Atmosphere Sea ice Exchanges and Teleconnections) focused on improving the representation of surface turbulent heat fluxes in polar regions. The research scientist will propose novel formulations for surface turbulent heat fluxes based on machine learning techniques and relying on data including both a wide dataset from previous polar experiments and observations from recent campaigns carried out within the YOPP framework. Machine-learning techniques of the regression type could be used, such as Multivariate Adaptive Regression Splines (MARS, Friedman, 1991) or Locally Estimated Scatterplot Smoothing (LOESS, Cleveland, 1981). Expertise of the candidate to select the most suitable method is very welcome. Knowledge about the physical parameters that should enter the algorithm can rely on local expertise.

Environment: The position will be held at CNRM (Centre National de Recherches Météorologiques) in Toulouse (France) in the GMGEC department (Groupe de Météorologie Grande Echelle et Climat) in the IOGA team (Interactions Océan-Glace-Atmosphère). The GMGEC department is at the forefront of climate modelling and contributes to each phase of the Coupled Model Intercomparison Project (CMIP) with its in-home coupled model, CNRM-CM, co-developed with CERFACS. The IOGA team aims at improving the representation of ocean, sea ice and atmosphere exchanges and interactions in the CNRM-CM model. IOGA contributes to the development of modelling tools used for climate predictions and projections and numerical weather predictions (for instance the SURFEX platform, used for air-ice and air-sea fluxes calculation and ocean-atmosphere coupling) and investigates coupled mechanisms and processes driving the climate system behaviour.

Required qualifications: Ph.D. or experience in statistics for climate

Knowledge about machine learning

Programming skill : scripting and visualisation (e.g. bash, R, python)

Good command of English.

Collaborative spirit and communication skill

Applications should be submitted through the CNRS portal : https://emploi.cnrs.fr/Offres/CDD/UMR3589-VIRGUE-006/Default.aspx?lang=EN

PhD positions in Artificial Intelligence (AI) for sustainable manufacturing

The Department of Data Science and Knowledge Engineering (DKE) at Maastricht University, the Netherlands, is looking for PhD candidates in AI for sustainable manufacturing.

In a joint collaboration with VDL Nedcar, the largest Dutch automotive manufacturing company, you will work in a team to investigate AI techniques within VDL Nedcar’s manufacturing environment. The ultimate goal is to make intelligent decisions in a transparent and reliable way, reduce costs, and save energy and reduce overall CO2 emissions. The developed AI technology will be embedded in a Digital Twin: a real-time simulation of VDL Nedcar’s battery line for the production of electronic vehicles.

As a PhD candidate, you will primarily address the following four topics: (1) planning & scheduling (2) prescriptive quality (3) predictive maintenance and (4) hybrid intelligence.

These PhD positions are part of the Green Transport Delta, a public-private innovation programme that aims to make Dutch transport sectors futureproof and sustainable. You will be embedded in the consortium around electrification, which focuses on improving various aspects of battery-powered electric transport as a key component of the transition to climate-neutral mobility.

You will be expected to:

- perform scientific research in AI for sustainable manufacturing as described above;

- publish results at (international) conferences and in international journals;

- collaborate with other group and faculty members;

- assist with educational tasks (e.g. assist in courses, supervise Bachelor/Master students).

Requirements

- MSc degree in Computer Science, Artificial Intelligence, Data Science, Applied Mathematics;

- Strong programming skills;

- Proficiency in English (oral and written);

- Excellent communication skills;

- Ability to collaborate in an international setting.

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 (€2.434 gross per month in first year to €3.111 in the fourth and final year). On top of this, there is an 8% holiday and an 8.3% year-end allowance. 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. Non-Dutch applicants could be eligible for a favorable tax treatment (30% rule).

Maastricht University. Maastricht University (UM) has around 22,000 students and 4,500 employees. Reflecting the university's strong international profile, a fair amount of both students and staff are from abroad. Research at UM is characterized by a multidisciplinary and thematic approach, and is concentrated in research institutes and schools. UM placed #6 in Times Higher Education’s (THE) Young Universities Ranking 2021, and #127 in THE’s World University Rankings 2022.

http://www.maastrichtuniversity.nl

The Department of Data Science and Knowledge Engineering. Founded in 1992, we are a fast-growing department undertaking internationally respected research in the areas of computer science, artificial intelligence, data science, robotics and applied mathematics. Much of our research takes place at the interfaces of these disciplines. We maintain a large network of industry partners and provide education through one bachelor’s programme and two master’s programmes.

Our new colleague(s) will be joining a tight-knit department consisting of ~70 principal investigators, postdocs and PhD students, 800 BSc and MSc students and a team of dedicated support staff members. Together, we come from over 40 different countries.

https://www.maastrichtuniversity.nl/dke

The Faculty of Science and Engineering. Maastricht University heavily invests in the growth of its STEM research and education. The Faculty of Science and Engineering – which houses the Department of Data Science and Knowledge Engineering - 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 fundamental physics, circularity and sustainability, data science and artificial intelligence.

https://www.maastrichtuniversity.nl/fse

Applicants are asked to prepare an application consisting of:

Your application must contain the following documents (all in English):

- 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 curriculum vitae;

- 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

Applications received by December 15, 2021 will receive full consideration. Applicants may be called in for an interview. We intend to fill this position as soon as possible; the starting date for this position is early, 2022.

Applications for these positions can be directed to: Prof. Mark Winands, [email protected] or

Prof. Frank Thuijsman, [email protected].​ ...

Title of the thesis: Contribution to modeling and support for the dynamic management of user-centric services in a smart building environment uncertain

Main host laboratory: Knowledge and Artificial Intelligence Laboratory

Distributed (CIAD) of the University of Technology of Belfort-Montbéliard and the University

Bourgogne Franche-Comté - http://www.ciad-lab.fr

Partner laboratory: Architecture, Urban Morphology and School Project Laboratory of Architecture of Strasbourg

Partner company (CIFRE contract): Kardham Digital, Paris

Specialty of the prepared doctorate: Computer science Keywords: multi-agent systems, building information modeling, user-centered modeling, user services

 A master's degree or equivalent in computer science, artificial intelligence or other related specialty

 A very good level of mastery in object-oriented programming is required (Java, C #, Python)

 Knowledge of multi-agent systems, machine learning, Internet of things will be appreciated

 Fluency in French (oral and written) required

 A good command of English (oral and written) is required

Practice locations: Kardham Company in Paris and CIAD Laboratory in Belfort

Funding: Fixed-term contract of 3 years in the company Kardham according to the terms

CIFRE-type financing

File to be sent by January 31, 2022

Estimated start of the thesis contract: September 2022

Possibility of having an internship or a fixed-term contract before official recruitment in September 2022.

Applications should be sent by email to:

 Prof. dr. Stéphane GALLAND [email protected]

 Dr. Emmanuel DUFRASNES [email protected]

 Dr. Nicolas COCHARD [email protected]

 Mr. Pascal ZERATES [email protected]

The application file must contain:

 a detailed CV

 a copy of the Master's degree or any document attesting to the Master's level

 a copy of the Master's transcripts

 a copy of the identity card or passport

 a cover letter, references and / or one to two letters of recommendation Incomplete applications will be rejected.

Senior Lecturer at Paris-Est Créteil University

An MCF post will be published in the 2022 synchronized session. The position will be attached to the LACL https://www.lacl.fr/fr/ and the teaching will be provided at EPISEN https://episen.u-pec.fr/

The candidate should integrate into the poles and research axes of the LACL SVS team. Particular attention will be paid to applications that meet one or more of the following criteria:

has. Strengthening of the controller synthesis pole for probabilistic and timed models and statistical methods for the synthesis and verification of cyber-physical systems.

b. Openness to new applications of formal methods in artificial intelligence, exclusively those promoted in the LAMAS/SR (e.g. https://lamassr.github.io/)or FMAI(https://www.doc.ic.ac.uk/~fbelard/Workshop/conferences).

c. Participation in laboratory research in the field of semantics of distributed systems.

Any other theme justifying a contribution to the laboratory's research will be considered.

Director of the LACL laboratory: Julien Cervelle ([email protected])

For teaching activities, the person recruited undertakes to take charge of:

1) The Introduction to Systems and Network Infrastructures course (engineer level 1st year).

2) One of the following courses (Engineer Level 3rd Year): - Network security

- Cloud et containerisation

- Data science/data engineering.

Any teaching experience in any of these courses will therefore be appreciated.

Also, at the end of 2 years of support by the current manager, the person recruited will have to take charge of the responsibility of the first year of the engineering degree in Information Systems.

Head of the Information Systems Department: Olivier Michel([email protected]). Responsible for the first year of the engineering cycle: Elisabeth Pelz([email protected]).

Hello everyone, We are looking to recruit an engineer (1-year fixed-term contract) to work on the realization of a glove allowing interaction by micro-gestures, as well as the realization of a demonstrator showing the use of this glove in different contexts.

To apply contact us directly by email by attaching CV and cover letter.

Do not hesitate to write to us if you have any questions and/or to distribute this offer to anyone potentially interested.

Alix Goguey and Laurence Nigay alix.goguey@univ-grenoble-alpe s.fr laurence.nigay@univ-grenoble-a lpes.fr ----------------------------- Job description Your mission will be to develop a robust prototype of a glove allowing human-machine interaction by micro-gestures (hand finger gestures).

Initially, the mission will consist in identifying a technical solution that will be the basis of the capture. Several prototypes have already been made, each prototype exploring a different capture solution. You will have access to all of our work already done and will work in collaboration with a team of researchers who have acquired expertise in this field. In a second step, the mission will consist in making several copies of a glove implementing the chosen technical solution, with the objective of a TRL 4 level of maturity. It is envisaged the filing of a patent on the capture system carried out.

Main missions: - Study of possible technical solutions - Realization of a glove allowing the capture of micro-gestures - Realization of a software layer allowing the use of micro-gesture events captured by the glove - Realization of a demonstrator illustrating the use of micro-gestures in various applications.

Skills sought: - Electronics - Computer development - Excellent skills in equipment and manufacturing Profile: - You hold a Bac + 5 Diploma in Electronics or Computer Science (Engineering School or University) - Quality: Autonomy, Ability to work in a team, appetite for research at the service of users.

Company: Floralis, a subsidiary of the Université Grenoble Alpes (100 p. > €10 million turnover) works on the development and transfer of new technologies from research laboratories and the management of industrial relations of research laboratories and in particular ensures the mission of operator of the Carnot Institute for Software and Intelligent Systems (iC LSI).

As part of the project entitled "iGlove" led by the Carnot Institute for Software and Intelligent Systems, we are recruiting a Design Engineer who will work within the IIHM (Engineering of Human-Machine Interaction) research team of the LIG laboratory, located in the university campus of Saint-Martin-d'Hères.

Dear colleagues, A PhD position (3 years) as part of the ANR DACE-DL project is open to applications at the LIRMM (Montpellier) in the field of hybrid AI and the semantic web (keywords: knowledge graphs, data linking, graph diving, machine learning, NLP).

The job description is

here: https://docs.google.com/document/d/e/2PACX-1vQGokw2DtCXp0IFe3S0QUGm-KIFHI6N50GnT4Wm-Jo9bFkWkRJaOCyCqwQuApTsYbb3BAC8eDm8g-38/pub#ftnt1

Please link the information to your students or potentially interested persons.

Sincerely, Konstantin Todorov

Title: Design and Development of Authoring Tools that Enable Teachers to Create their Custom Extended Reality Applications

Research Laboratory Computer Laboratory of the University of Le Mans (LIUM) Technology Enhanced Learning Team

Location of the Post-Doctorate IUT de Laval - CERIUM2 building 52 rue des Docteurs Calmette et Guérin 53020 Laval France

Supervisor Iza MARFISI ([email protected])

Dates From the 15th of February 2022 to 15th of July 2023 (18 months)

Keywords: Extended Reality, Mixed Reality, Augmented Reality, authoring tools, Human- Computer Interactions, Technoplogy Enhanced Learning.

Description of the research subject

EXtended Reality (XR) represents the wide spectrum of innovative Human-Computer Interactions (HCI) ranging from Augmented Reality to Virtual Reality. XR potentially offers numerous advantages in terms of learning, collaboration and motivation. However, the creation of such applications is too complex for teachers, in terms of design and development.

Ideally, their creation involves a team of experts including at least a teacher, a programmer specialized in XR, a graphic designer and, if possible a game designer and a UX designer to create engaging and fun learning experiences.

This team needs to imagine a scenario that supports learning and design XR interactions that are adapted to the pedagogical objectives, the learners and the context in which they will be used.

However, it is very rare for schools to be able to hire such a team, and teachers often need to go through this process alone.

The MIXAP project, in which the postdoc will take place, aims to provide methods and authoring tools to help teachers create their own XR applications, in order to take advantage of their numerous pedagogical advantages. It is financed by Le Mans University and the Pays de la Loire Region, as part of the “Etoile Montante” program.

The postdoc will be able to build on 3 current projects conducted at LIUM: - SMART-Fractions: a Mixed Reality game for learning fractions

- SituLearn: a project that offers tools to support collaborative learning and the follow- up of students during field trips

- TGRIS: a Virtual Reality interview Simulator to learn how to deal with emotionally intense situations

The objective is to analyze these applications to determine generic models that could be used in other educational contexts. Following the Design-Based Method involving local schools, the postdoc will then design and develop the authoring tools so that any teacher can design their own custom XR applications.

Candidate profile We are looking for a researcher who holds a PhD in the field of Computer Science, with experience in Technology Enhanced Learning and Innovative Human Computer Interactions.

The candidate must have defended his PhD less than 3 years before the beginning of the Postdoctorate (after the 15th of February 2019).

The candidate is not required to speak French although it would be an advantage to communicate with the local teachers during the co-design and testing phases.

The postdoc will earn € 2,849.10 BRUT / month.

The project also involves a 2-week research visit in a partner lab, in Canada or Japan.

Nature of the competition: Lecturer

Job Number: 0468

CNU Section(s): 27th

Assignment component (location): UFR Sciences et Technique – Campus Dijon – Mirande

Host laboratory: Laboratoire d'Informatique de Bourgogne (LIB) - EA 7534

Requested appointment date: September 1, 2022

Vacancy: vacant

Publication Profile: Complex Systems

Profil en Anglais / « Job Profil » : Complex Systems

The IEM department (Computer Science, Electronics, Mechanics) of the UFR Sciences and Techniques offers a complete training course in computer science: Computer Science License (L1, L2, and L3) and Master computer science with two courses: Databases and artificial intelligence and Image and artificial intelligence. The alternation is offered in Master (M1 and M2). A project to open a Health and Artificial Intelligence course in English is underway (2021-2022 academic year), in collaboration with the UFR Sciences de Santé.

The I.E.M. department also includes a professional license (Computer Science Professions).

The candidate recruited will strengthen the teaching team of the Bachelor's degree (L1, L2 and L3) and the Master in Computer Science. He will intervene primarily in the pedagogical teams for the teaching of system, distributed systems and networks (in bachelor and master) and in the teaching of programming and algorithmic in bachelor and master. He will also join the pedagogical team of the professional license for these courses.

He/She is intended to be responsible for teaching units in bachelor's and master's degrees. He/She will also have to participate in the supervision of tutored projects and the follow-up of work-study students, particularly in M1.

Teaching contacts: Nadine Cullot – Deputy Director of the IEM Department – [email protected]

The candidate recruited will join the LIB laboratory (Laboratoire d'Informatique de Bourgogne) of the University of Burgundy (Dijon). He/she will develop his/her research activities in the Data Sciences team in connection with the transversal themes of complex systems.

In this context, the person recruited will have to demonstrate a high-level know-how and mastery in data science, network science, complex systems, computational sciences. He/She will be familiar with scientific approaches at the interface of several disciplines (Computer Science, Health, Sociology, Transport, etc.). He/Shewill participate in the structuring and development of the laboratory's multidisciplinary projects by promoting interactions between experimental approaches (biology, medicine, cognitive sciences, social sciences, etc.) and modeling sciences (computer science, mathematics).

The lecturer should contribute to strengthening existing research activities and/or coherently develop new orientations. The ability to invest in new projects (Region, ANR, Europe, Industrial, etc.) will be one of the decisive elements of recruitment. He/She will be involved in the regional, national and international scientific actions of the data science team in the field of complex systems.

The profile of this position is part of the themes supported by the site policy of the federal university UBFC (University of Bourgogne Franche-Comté) through its "Fundamental, Applied and Technological Sciences" division.

Job Designation:

Nature of the competition: Lecturer

Job Number: 1159

CNU Section(s): 27th

Assignment component (location): UFR Sciences et Technique – Campus Dijon - Mirande

Host laboratory: Laboratoire d'Informatique de Bourgogne (LIB) - EA 7534

Requested appointment date: September 1, 2022

Vacancy: likely to be vacant

Publication profile: Management of massive, distributed, heterogeneous data: architectures, data models and knowledge

Profil en Anglais / « Job Profil » : Management of massive, distributed, heterogeneous data: architectures, data models and knowledge

Pedagogical objectives and coaching needs: The IEM department (Computer Science, Electronics, Mechanics) of the UFR Sciences and Techniques offers a complete training course in computer science: Computer Science License (L1, L2, and L3) and Master computer science with two courses: Databases and artificial intelligence and Image and artificial intelligence. The alternation is offered in Master (M1 and M2). It also includes a professional license (Computer Science Professions).

The candidate recruited will strengthen the teaching team of the Bachelor's degree (L3) and the Master's degree in Computer Science. It will have to intervene primarily on themes related to data storage: Database management systems, NoSQL databases, Data management in distributed environments, Data warehouse. Artificial Intelligence skills in data analysis would be appreciated. He/She will also strengthen the teaching teams in L1 and L2 (programming, object-oriented programming, advanced algorithms). He/She is expected to be quickly responsible for teaching units in bachelor's and master's degrees.

Teaching contacts: Nadine Cullot – Deputy Director of the IEM Department – [email protected]

Research The candidate recruited must integrate into the LIB laboratory (Laboratoire d'Informatique de Bourgogne) of the University of Burgundy (Dijon). He will develop his research activities in the Data Sciences team.

The LIB Data Science team conducts innovative and recognized work in applied areas such as the analysis of digital social media data, the combination of symbolic and digital AI techniques to improve analysis techniques.

The team relies on an original positioning exploiting multi-paradigm approaches for the storage(polystore)or the interprosage(data warehouse, data lake)of massive data and real-time processing techniques(stream processing)for data analysis with graph algorithms, machine learning possibly coupled with ontologies or reasoning mechanisms.

The profile of this position is part of the themes supported by the site policy of the federal university UBFC (University of Bourgogne Franche-Comté) through its "Fundamental, Applied and Technological Sciences" division.

Research contacts:

Olivier Togni – Director of lib – [email protected]

Hocine Cherifi – Deputy Director of the LIB – [email protected]

Eric Leclercq – Head of the LIB Data Science team - [email protected]

Dear all, We have a postdoc opening on developing Arabic handwritten text recognition systems at the NC State University, North Carolina, USA.

No Arabic knowledge is needed but please make sure that you are good at deep learning and you are in one of the following fields: document analysis, computer vision, and image processing. You will be jointly supervised by a humanity faculty member and an ECE faculty member (me).

More details about the opening including the application link can be found here: https://jobs.ncsu.edu/postings/152807

If you have any questions, please don't hesitate to let me know. I also highly appreciate it if you could forward this opening to relevant parties.

Sincerely, Chau-Wai Wong

Assistant Professor ECE, NC State University