Associate Professor in ‘Data Science and Statistical learning‘

Laboratoire d'Informatique, de Modélisation et d'Optimisation des Systèmes (CNRS UMR 6158) Institut Henri FAYOL Open position of Associate Professor in ‘Data Science and Statistical learning‘ Mines Saint-Etienne (MSE), one of the graduate schools of Institut Mines Télécom, the #1 group of graduate schools of engineering and management in France under the supervision of the Ministry of the Economy, Industry and Digital Technology, is assigned missions of education, research and innovation, transfer to industry and scientific, technological and industrial culture. MSE consists of 2,400 graduate and postgraduate students, 400 staff (150 Faculty), a consolidated budget of €46M, 3 Campuses dedicated to i/ Industry in Saint-Etienne and Lyon (Auvergne Rhone-Alpes region) ii/ Microeletronics and connected objects in Gardanne (Aix Marseille Provence metropolitan area, SUD region) and iii/ Health Engineering in Saint-Etienne ; six research units ; five teaching and research centres and a science center: “La Rotonde” leader in France (> 50,000 visitors). Since 2019, MSE has been ranked around 400th worldwide in Engineering and Technology by the Time Higher Education (#1 higher education institution in both of its regions), and #1 in France for the Sustainable Development Goals (SDG) 11-Sustainable cities and communities and 13-Climate Action. Its work environment is characterised by high Faculty-to-Student, Staff-to-Faculty and PhD-to-Faculty ratios, as well as comprehensive state-of-the-art experimental and computational facilities. Member if the T.I.M.E. association of technological universities, MSE has +150 active international partnerships. As part of Institut Mines-Telecom, MSE is a member of the European University EULIST. Its strategy for the next 5 years is oriented towards helping businesses and the society undergo the major ecological, digital and generational transitions ahead, as well as fostering national and European sovereignty in microelectronics, through education, research, technology transfer and science outreach. The Laboratory of Computer Science, Systems Modelling and Optimization (LIMOS ), is a Mixed Research Unit (UMR 6158) in computer science, and more generally in Science and Information and Communication Technologies (STIC). It is linked with the Institute of Information Sciences and their Interactions (INS2I) of the CNRS and in a secondary way with the Institute of Engineering and Systems Sciences (INSIS). The LIMOS belongs to the University Clermont Auvergne (UCA) and Mines Saint-Etienne (MSE). It is also a member of Clermont Auvergne INP. The scientific positioning of LIMOS is centered on Computer science, Modeling and Optimization of Organizational and Living Systems. Founded in 2011, the Henri Fayol Institute , brings together academics in industrial engineering, IT, environment and management to work on the theme of the global performance of companies. From a sustainable development and social responsibility perspective, a company's performance must be considered not only from a technical and economic standpoint, but also from a social, environmental and territorial standpoint. Two technological platforms have been developed to validate, promote and teach the work done within the institute under near-real conditions. The first one is dedicated to the territory of the future (Territoire Platform ) and the second one deals with the industry of the future (IT'mFactory Platform ). Mines Saint-Etienne is recruiting an Associate Professor in Data Science and statistical learning, artificial intelligent for industry and territories of the future. The proposed position is open within the GMI (Mathematical and Industrial Engineering) department of the Henri Fayol Institute with research activities developed in the SIC axis of the UMR CNRS 6158 LIMOS. The aim is to strengthen the skills of Mines Saint-Etienne in applied mathematics, particularly in data science and statistical learning, and in artificial intelligence, in relation to industry and the territories of the future, through the identification and optimal design of industrial systems from both a research and teaching perspective. The missions of this position will be carried out on the Saint-Etienne campus (42, France). 1) Candidate profile The candidate, who holds a PhD in Applied Mathematics or Data Science (CNU sections 26, or 27, or 61) or equivalent. A French CNU habilitation in section(s) (CNU n°26, n°27, n°61) will be considered but is not mandatory. Significant teaching experience in the fields listed below (instructor, temporary assistant and/or ATER) at the graduate level will be appreciated. The candidate should have strong skills in the following areas: Data Science and/or Statistical Learning from complex data {massive data, heterogeneous data, time series, graphs, data flows, imprecise or uncertain data, and functional data,…}, Artificial Intelligence. Postdoctoral experience will be highly appreciated. Command of the English language is essential. Given the School’s international development projects, a significant international experience is strongly favoured. Otherwise, an international mobility with a foreign partner institution should be carried-out during the three years following recruitment. The following traits will be important assets: - Interest for teamwork and willingness to elaborate one’s research project in this context - Interest in industrial relations, transfer and innovation - Appeal for interdisciplinarity and multi-discipline collaborations - Practical common sense, openness and intellectual curiosity - The quality of oral and written communication 2) Missions The position will strengthen and develop a research mission and a teaching mission. The research and teaching activities will be carried out on the Saint-Etienne (42) campus. Occasional involvement in the other campus’ activities is possible and encouraged. Associated transport and accommodation costs will be covered if necessary. o Teaching The teaching mission consists of providing courses, tutorials and practical work in the teaching of mathematics in initial training for the Ingénieur Civil des Mines (ICM) cursus in the fields of probability and statistics, data science, industrial statistics and numerical methods as well as project and internship supervision. The courses may also concern more specialized master's degree courses, master's degree in ‘Maths in Action’, doctoral training, continuing education and under salaried status, specialized master's degree in Industrial Transition Management. Teaching in English is also possible. The demand for data science with training profiles around ‘data scientist’ and ‘data analyst’ increases the pressure on the 3 years of the ICM cycle and the masters. One of the challenges is to integrate data science with digital and AI developments in the Ingénieur Civil des Mines (ICM) cursus from the first year of training. Active involvement in the teaching teams is expected. The design of new activities and the development of innovative teaching methods, in particular involving digital technology, will be an integral part of the teaching mission. The candidate should be able deliver courses, seminars, tutoring, project-based activities and MOOCs in English. A minimum number of hours must be completed yearly. Course (re-)design, supervision and team management activities are included in the teaching hours log. o Research The research missions will take place in the SIC axis of LIMOS, dedicated to data acquisition, management and analysis of large masses of data on the one hand, and to the development of data mining and statistical and automatic learning techniques on the other hand. The work of the Information and Communication Systems (SIC) axis focuses on fundamental and applied issues related to data acquisition via wireless sensor networks and their security, management and analysis of large amounts of data, as well as systems analysis (quality, interoperability), particularly through web services and business processes. More specifically, the candidate recruited will be able to integrate into the "Data, Services and Intelligence (DSI)" theme, dedicated to issues related to the management and optimization of large amounts of data and their analysis via data mining and machine learning techniques and modeling, as well as to the analysis and verification of applications (web services and business processes). The person recruited will develop work in data science and statistical learning, using complex data (massive data, heterogeneous data, time series, graphs, data flows, imprecise or uncertain data, functional data), Artificial Intelligence, while taking into account the interaction with humans by developing explainable solutions. The research contribution could be made in different forms: theoretical developments, applications and prototype developments (packages in different scripting languages etc…). The candidate will have to contribute to reinforce the existing research activities. More than a fine adequacy to the profile, the LIMOS will privilege the quality of the candidates and their capacity to produce a high level research within the laboratory. o Missions of the candidate The following missions will be entrusted to the candidate: - To carry out research activities related to data science and in particular in numerous projects led by Mines Saint-Etienne such as the existing research chaires (Ciroquo , VALADoE , Corenstock ) and numerous projects around industrial systems (robotization, optimal system design, reliability, process control, risk analysis,...). - Actively participate in collaborative projects of the department and the school in the field of data sciences, AI and the industry of the future. - Participate in setting up new projects and industrial collaborations. - Quickly take on the co-supervision of theses and participate in the research activities of the axis. - The candidate's medium-term objective will be to defend a HDR habilitation to direct research. - The candidate will demonstrate his or her ability to develop and to carry out and supervise world-class research and to achieve international recognition in his/her field within the few years following his/her appointment. An original research project will be favorably considered if its relevance to the strategy of the institution and the laboratory is demonstrated. 3) Candidate assessment criteria The main evaluation criteria are (non-comprehensive list): · PhD in Applied Mathematics or Data Science (CNU sections 26 - 27 - 61) · Ability to strengthen activities and projects in connection with the 4 research chairs. · Ability to fit into the project of the GMI department of the Institut Fayol and the SIC axis of LIMOS and to strengthen the position of Mines Saint-Etienne in the field of data science and statistical learning. · Capacity to reinforce the theme and to inscribe its activities in the applied mathematical tools associated with Digital Sciences and AI for the industry of the future. · Scientific production: quality and impact of publications in journals and conferences indexed by the main electronic databases (Scopus, Web of Science, PubMed, Nature Index, arXiv.org ...). · Willingness to deploy research compatible with the 5 objectives of the European Union: quality, impact, diversity, inclusiveness and collaboration. · Demonstrated experience or willingness to develop partnership research: direct industrial partnerships, collaborative research, start-up support. · Significant teaching experience (as an instructor, visiting professor and/or ATER) in the above fields at the graduate level. · Experience in producing digital courses, books, and experience in developing and using new forms of teaching in the above-mentioned areas at the graduate level will be appreciated. · Fluency in English. · International experience or partnerships are desirable. · Ability to work collaboratively · Ability to defend the French accreditation to supervise research (Habilitation à Diriger des Recherches/ HDR) qualification in the five to seven years following the appointment 4) Recruitment Conditions ‑ Permanent public law contract. ‑ Remuneration is based on the rules set out in the Institut Mines Télécom collective labour agreement. ‑ Candidates should hold a doctorate diploma or a similar recognized qualification level, equivalent to the required national diplomas. ‑ Required date for taking up the position: October 1st , 2023. 5) Application procedures The application file should include: - An application cover letter - A curriculum vitae outlining teaching activities, research work and where appropriate, relations with economic and industrial sectors (maximum 10 pages) - Recommendation letters, at the discretion of the candidate, - A copy of the Doctorate diploma (or PhD), - A copy of an identity document These documents should be submitted on the platform RECRUITEE by April 14th, 2023 at the latest URL: https://institutminestelecom.recruitee.com/o/maitre-de-conferences-en-sciences-des-donnees-et-apprentissage-statistique-fh Candidates selected for an interview will be informed rapidly. Part of the interview will be held in English. Cover letters, CVs and application files written in English will be accepted, but applicants will have to demonstrate in their application file their operative ability to communicate in French with students, fellow faculty members and the school administration. For those invited to be interviewed, the same will be expected in oral form and tested by the selection committee. 6) Further information For further information concerning the position, contact: - Head of SIC Axis (UMR LIMOS) : Pr. Engelbert MEPHU NGUIFO, Tel: +33 (0)4 73 40 76 29, E-mail: engelbert.mephu_nguifo@uca.fr - Director of Henri Fayol Institute:: Pr. Olivier BOISSIER, Tel: +33 (0)4 77 42 66 14, E-mail: olivier.boissier@emse.fr - Head of GMI Team: Pr. Mireille BATTON-HUBERT, Tel: +33 (0)4 77 42 00 93, E-mail: mireille.batton-hubert@emse.fr For further administrative information, contact: - Amandine HIRONDEAU Tel + 33 477 42 01 03 E-mail hirondeau@emse.fr - Milica PETKOVIC Tel+ 33 (0)4 77 42 00 81 Mel milica.petkovic@emse.fr - Julie JAFFRE Tel+ 33 (0)4 77 42 00 17 Mel julie.jaffre@emse.fr Our data protection policy (in French): https://www.mines-stetienne.fr/wp-content/uploads/2018/12/Informations-des-candidats-sur-les-traitements-de-donn%C3%A9es-personnelles.pdf

Last updated: 16 February 2023