Junior Professorship F/H (IA-MEP - Trusted IA for personalized medicine)

Contract type : Fixed-term contract

Level of qualifications required : PhD or equivalent

Fonction : Tempary Research Position

Corps d'accueil : Ingénieur de Recherche (IR)

Level of experience : Recently graduated

About the research centre or Inria department

The Inria Center at Université Côte d'Azur includes 42 research teams and 9 support services. The center’s staff (about 500 people) is made up of scientists of different nationalities, engineers, technicians and administrative staff. The teams are mainly located on the university campuses of Sophia Antipolis and Nice as well as Montpellier, in close
collaboration with research and higher education laboratories and establishments (Université Côte d'Azur, CNRS, INRAE, INSERM ...), as well as regional economic players.


With a presence in the fields of computational neuroscience and biology, data science and modeling, software engineering and certification, as well as collaborative robotics, the Inria Centre at Université Côte d'Azur is a major player in terms of scientific excellence through its results and collaborations at both European and international levels.

Assignment

The person recruited will be responsible for strengthening expertise in artificial intelligence for digital health, with a particular focus on causal and federated learning, medical data confidentiality, and the development of AI-driven decision-support tools.


She/he will contribute to advancing the research priorities of the PreMeDICaL team, integrating their expertise into ongoing projects such as PEPR programs (SMATCH, DIGHPATH, SSF-ML-DH, and IPoP) and national initiatives like FedMalin.


In addition, she/he will be responsible for expanding international collaborations, supervising PhD and postdoctoral students, and fostering partnerships with academic and industrial stakeholders.

The recruited candidate will play a pivotal role in developing AI-driven solutions for precision medicine, ensuring ethical and trustworthy AI applications while addressing challenges related to data sovereignty, fairness, robustness, and interpretability.


From a teaching point of view, the person recruited will provide support to the teaching team of the University of Montpellier, contributing to Master’s programs in AI & Data Science, Statistics & Data Science, and digital engineering at Polytech Montpellier.

She/he will also be involved in interdisciplinary programs such as Epidemiology, Health Data, and Biostatistics (EDSB), as well as IDIL tracks like Digital & Movement Sciences for Health.

The candidate will be responsible for developing and disseminating courses on foundation models, privacy-
preserving AI, and causal machine learning, and will contribute to continuing education initiatives such as Inria
Academy.


The digital health and AI for healthcare theme is a priority for the University of Montpellier, and the chair project is an
opportunity to federate the site in terms of interdisciplinary research, innovation, and knowledge transfer.

The project aligns with regional and national strategies, including AI for Health in the Occitanie region, and will
enhance the international visibility of PreMeDICaL, Inria, IDESP, and the Montpellier research ecosystem.


By integrating into existing networks such as Data & Life Science, ExposUM, and CHU Montpellier, the chair will drive
cutting-edge research and innovation in AI-driven healthcare
solutions.

Main activities

  •  Conduct research in the field of data sciences applied to public health, disseminate results and ensure their impact on public health stakeholders;
  • Supervision of doctoral students, post-doctoral fellows and engineers. Setting up and participating in collaborative research contracts;
  • Participate in the training of students in courses linking mathematics and health or engineering and health;
  • Leading and creating links between players in the digital and public health fields, with the objective of setting up a new project-team on the subject

 

 

Skills

KNOWLEDGE

  • Scientific skills and level required: PhD in mathematics, statistics, Machine Learning, applied mathematics or data science, followed by at least 1 year’s research experience,
  • Experience of working with public health or clinical data,
  • Fluency in written and spoken scientific English.


KNOW-HOW

  • Ability to develop a network of contacts and partnerships,
  • Ability to work as part of a team or to lead a team,
  • Ability to initiate, set up and manage projects.

Benefits package

  • Subsidized meals
  • Partial reimbursement of public transport costs
  • Leave: 7 weeks of annual leave + 10 extra days off due to RTT (statutory reduction in working hours) + possibility of exceptional leave (sick children, moving home, etc.)
  • Possibility of teleworking (after 6 months of employment) and flexible organization of working hours
  • Professional equipment available (videoconferencing, loan of computer equipment, etc.)
  • Social, cultural and sports events and activities
  • Access to vocational training
  • Social security coverage

Remuneration

According to experience