Assistant Professor / Lecturer in machine learning applied to biosignal processing M/F

IMT Mines Ales; France; Sur place; EUR 40 000 - 60 000; Plein temps

Résumé du poste

A prestigious engineering institution in France is seeking a Senior Lecturer in machine learning applied to biosignals. The candidate will engage in teaching, research, and technology transfer, focusing on machine learning applications and human biosignal analysis. This full-time, permanent position offers various benefits and a vibrant academic ecosystem.

Prestations

75% of public transportation costs covered

Sustainable mobility package

Wide range of social benefits

Stimulating innovation ecosystem

Ideal environment for pursuing passions

Qualifications

• Significant teaching experience in research areas related to AI and machine learning.
• Ability to conduct experimental protocols with human participants.
• Experience publishing in international journals.

Responsabilités

• Develop and teach advanced courses in AI and machine learning.
• Supervise research projects and internships.
• Participate in major academic assessments and thesis defenses.

Connaissances

Applied mathematics

Machine learning

Biosignal processing

Research and development

Signal processing

Teamwork

Formation

PhD in relevant field

Outils

Python

TensorFlow

PyTorch

Description du poste

Organisation/Company IMT Mines Ales Department Human Ressources Department Research Field Computer science » Other Researcher Profile Leading Researcher (R4) Positions PhD Positions Country France Application Deadline 15 Dec 2025 - 00:00 (UTC) Type of Contract Permanent Job Status Full-time Offer Starting Date 2 Mar 2026 Is the job funded through the EU Research Framework Programme? NextGenerationEU Is the Job related to staff position within a Research Infrastructure? No

Offer Description

Come and join IMT Mines Alès, a prestigious engineering school that ranks among the best in France and worldwide, based in Alès, a town on a human scale, the capital of the Cévennes, where the quality of life is highly appreciated by its inhabitants.

You will join CERIS.

As a Senior Lecturer at the Institut Mines‑Télécom, you will be involved in teaching, research and technology transfer.

Teaching activities

Teacher‑researchers at Institut Mines‑Télécom are responsible for developing teaching programs, coordinating teaching teams, and leading initiatives in educational innovation. The successful candidate will therefore be required to participate, depending on their areas of expertise, in the school's teaching activities, which include:

• General engineering training, Initial Training under Student Status (FISE);
• Specialized engineering training, Initial Training under Apprenticeship Status (FISA);
• Specialized training (master's degrees, specialized master's degrees, continuing education);
• Doctoral training.

Your expertise in applied mathematics, machine learning, and biosignal processing will be an essential asset for the 2IA department's courses, particularly in the modules dedicated to machine learning and the "cognitive engineer" specialty. This specialization aims to train experts in artificial intelligence capable of designing innovative solutions that facilitate user support in their professional and daily activities. This resolutely interdisciplinary program includes courses on human factors, the cognitive uses of technology, and the perception of human‑machine interaction from psychological, ethical, and legal perspectives.

You will also be able to contribute to the Teaching Units (UE) of the 2IA department, particularly those that include Teaching Unit Components (ECUE) related to machine learning, applied mathematics, or signal processing.

The successful candidate will be responsible for coordinating certain UEs related to artificial intelligence and data science, as well as teaching some of the courses in these fields (ECUEs). They will be able to contribute to teaching and educational exercises in the 2IA department, such as:

• Introduction to machine learning for the Computer Science and Networks (InfRes) program through apprenticeship;
• Supervision of research projects: R&D and technical studies;
• Introduction to machine learning (S8 – bachelor's degree level);
• Advanced machine learning (team supervision of the hackathon‑S9 – MSc level);

Teaching in one or more of the department's specializations open to S10 (MSc level): Image analysis and processing (program currently being redesigned); Natural language and speech processing; Deep learning/reinforcement learning, cognitive engineer.

Teaching for non‑specialist students is also expected, particularly within elective tracks offered in the core curriculum of the FISE (Initial Training under Student Status) and FISA (Initial Training under Apprentice Status):

• ECUE "Fundamentals of AI" (lectures/tutorials/practicals in flipped classroom format, parallelized for classes of 140 to 250 students);
• ECUE "Algorithms and Object Programming" (lectures/tutorials/practicals projects in flipped classroom teaching, parallelized for classes of 250 students);
• Your knowledge may also be used for other FISE core courses (signal processing, statistics, operational research).

The successful candidate will participate in major teaching activities such as juries and thesis defenses and will be asked from time to time to participate in other teaching activities and exercises at the school (supervision of core field assignments, projects, internships, academic tutoring). Some of the teaching may be conducted in English, using active teaching methods.

As a guide, participation in teaching activities represents an average of around 150 hours per year for a teacher‑researcher.

The successful candidate will be expected to supervise applied research projects (research and development assignments or technical studies), as well as internships and apprenticeship support. They will also participate in major academic assessments such as juries and thesis defenses and may be asked to participate in other educational activities at the school, including supervising field missions, projects, and academic tutoring.

Research activities

In line with the scientific orientations of CERIS and the EuroMov DHM research unit, the successful candidate will conduct work focused on the application of machine learning and deep learning to the analysis and modeling of human biosignals (EEG, EMG, ECG, NIRS, HRV, etc.). The main objective will be to design, optimize, and interpret machine learning models capable of characterizing the cerebral, physiological, and behavioral dynamics associated with movement and health.

The work may focus on:

• The development of deep models integrating multiple sources of physiological and behavioral data for the assessment or prediction of sensorimotor performance;
• The exploration of self‑supervised or transfer learning methods adapted to low‑label data;
• The interpretability and reliability of AI models in the context of digital health, via explainable AI (XAI) and trustworthy AI approaches;
• Designing processing pipelines that leverage deep learning for time series and adaptive spectro‑temporal analysis (CNN, LSTM, Transformers, etc.);
• Optimization of models for real‑time or embedded environments, particularly in human‑system interaction or cognitive assistance devices.

This research will be part of EuroMov DHM's MIB&Co (Monitoring and Improvement of Behavior and Cognition) theme, at the interface between computational neuroscience, neuroergonomics, and artificial intelligence. It will aim to better understand human plasticity through the prism of movement, while contributing to the design of intelligent systems capable of continuous adaptation and learning.

The successful candidate will be required to:

• Design and conduct experimental protocols involving multimodal recordings on human participants;
• Actively participate in the scientific and technical operation of EuroMov DHM platforms (acquisition, synchronization, and preprocessing of biosignals);
• Publish in leading international journals and conferences in machine learning, physiological signal processing, digital health, and computational neuroscience;
• Develop collaborative projects with academic and industrial partners around AI for health and human movement.

This work will contribute to the innovative momentum of the EuroMov DHM unit and to the scientific visibility of IMT Mines Alès in the field of machine learning applied to biosignals and digital health.

Technology transfer and commercialization activities

Research activities must be subject to standard academic promotion, e.g., publications in journals and conferences, and participation in GdR and IMT communities . The person recruited will also be responsible for getting involved in commercialization activities with partner companies. This may include industrial chairs, setting up and participating in research contracts with industrial partners, or drafting funding applications to public bodies or international programs.

In addition, the person must be able to understand the process of commercial exploitation of research results in order to identify opportunities to contribute to cooperation between academic research, industrial research, and innovation sectors.

Finally, the successful candidate will be required to carry out, within their field of scientific and technical expertise, actions designed to support companies or the IMT Mines Alès incubator in order to promote the creation of spin‑offs and the development of technology companies.

• Significant teaching experience in the Center's research areas and topics, particularly those relevant to the position;
• Ability to work in a team of teachers and develop teaching approaches tailored to specific needs;
• Ability to teach while taking into account pedagogical alignment (skills, learning objectives and methods, assessment);
• Knowledge and practice of written and oral communication in English;
• Processing of biosignals;
• Experience in neuroscience;
• Interest in interdisciplinary collaborations;
• Significant research experience in the Center's fields and research topics, particularly those relevant to the position;
• Proven experience contributing to research projects with scientific output (publications, conferences, etc.);
• One (or more) international experience(s) would be a plus;
• Ability to establish scientific collaborations on experimental research projects;
• Ability to promote research work and transfer technology or knowledge to industrial partners;

Behavioral and interpersonal skills

• Autonomy
• Commitment
• Teamwork
• Organizational skills
• Rigorous and methodical
• Initiative
• Creativity and innovation

Specific Requirements

Recruitment is open in the discipline of "Computer Science – Artificial Intelligence – Machine Learning."

The position offered by IMT Mines Alès is a full‑time, permanent contract under public law, subject to the provisions of the Institut Mines‑Télécom management framework, in the role of Senior Lecturer, category C, class 2.

Salary: to be determined based on profile and experience

Internal Application form(s) needed

FP - Lecturer in machine learning applied to biosignal.pdf

• 75% of public transportation costs covered
• Sustainable mobility package for carpooling or cycling to work
• Wide range of social benefits
• Stimulating innovation ecosystem (startups, students, research, businesses, etc.)
• Ideal environment for pursuing your passions (sea/mountains nearby)

Selection process

Indicative date of the pre‑selection committee (without the presence of candidates): January 8, 2026

Eligible candidates will be notified as soon as possible after this date.

Indicative date of the recruitment committee (interviews with eligible candidates): 01/23/2026

The admissions committee's ranking will be published immediately after the committee meeting.