Research Fellow in Statistics and Modeling (M/F)

CNRS; France; Sur place; EUR 32 000 - 42 000; Plein temps

Résumé du poste

CNRS in Grenoble invites applications for a First Stage Researcher (R1) in the DATA department of the Jean Kuntzmann Laboratory. The project focuses on novel algorithmic approaches for physiological data–driven energy balance modeling and robust, scalable modeling frameworks.

The candidate will design statistical models, perform experimental evaluation, and document research with rigorous notebooks and version control.

Qualifications

• PhD in Statistics, Artificial Intelligence, Mathematics, Computational Modeling, or closely related discipline.
• Experience analyzing and modeling complex data in healthcare, biomedical sciences, or industry.

Responsabilités

• Design and develop advanced statistical models and algorithmic methods.
• Conduct iterative experiments, evaluation, and validation of models.

Connaissances

Analytical thinking

Independent work

Critical thinking

Research communication

Formation

PhD in Statistics

Outils

R

Python

Julia

Description du poste

Organisation/Company CNRS Department Laboratoire Jean Kuntzmann Research Field Mathematics Researcher Profile First Stage Researcher (R1) Application Deadline 1 Oct 2026 - 23:59 (UTC) Country France Type of Contract Temporary Job Status Full-time Hours Per Week 35 Offer Starting Date 1 Nov 2026 Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No

Offer Description

The successful candidate will be expected to generate novel scientific knowledge and develop innovative algorithmic approaches that advance the current state of the art in physiological data–driven energy balance modeling. They will play a key role in the design, development, experimental evaluation, validation, and continuous refinement of the proposed models. Through sustained scientific and methodological contributions, the researcher will help establish robust, interpretable, and scalable modeling frameworks capable of addressing complex physiological processes and supporting the project's long-term research objectives.

• Research design and development: Design and develop advanced statistical models, algorithmic methods, and software architectures that extend beyond commercially available or off-the-shelf solutions.
• Experimental research: Conduct iterative research and development cycles—including implementation, experimentation, and validation to design prototypes and proof-of-concept demonstrators for testing and refining scientific hypotheses.
• Addressing scientific challenges: Identify and overcome key scientific and technical barriers affecting the feasibility, performance, robustness, interpretability, and generalizability of the proposed models.
• Scientific literature review: Perform comprehensive and systematic reviews of the scientific literature to inform research activities and maintain expertise at the forefront of the field.
• Research documentation and knowledge dissemination: Produce high-quality technical documentation, justify methodological choices, and actively contribute to the maintenance of electronic laboratory notebooks and research records, including version control commits, development logs, and reproducible documentation.

You will join the DATA department of the Jean Kuntzmann Laboratory and collaborate closely with MIRA and the TEAM-C laboratory. MIRA develops cutting‑edge technological and software solutions, supported by ongoing research and innovation activities at the intersection of physiology, biology, nutrition, and sport science. This 9-month fixed‑term contract will be followed by another 9-month fixed‑term contract with MIRA, located in Grenoble.

• PhD in Statistics, Artificial Intelligence, Mathematics, Computational Modeling, or a closely related discipline, with demonstrated experience in the analysis and modeling of complex data within high‑impact application domains such as healthcare, biomedical sciences, or industry.
• Strong knowledge of, or a demonstrated interest in, physiology, health sciences, and data derived from physical activity and sports performance.
• Demonstrated commitment to rigorous research practices, including comprehensive documentation, traceability, and high‑quality scientific writing.
• High degree of technical autonomy, strong organizational skills, and the ability to manage research activities independently.
• Excellent critical thinking and analytical skills, with the ability to objectively interpret experimental outcomes, whether positive or negative.
• Proficiency in one or more scientific programming languages, including R, Python, and/or Julia.
• Sound knowledge of research project management methodologies and collaborative scientific workflows.
• English language proficiency at **CEFR B2** level or higher.