Postdoctoral Fellow in UnStrain: Revealing mobility tensions through representation learning - 18-month fixed-term contract

About Télécom SudParis:

Télécom SudParis is a prestigious public engineering school recognized at the highest level of digital science and technology. The quality of its training programs is based on the scientific excellence of its faculty and a teaching approach that emphasizes team projects, disruptive innovation, and entrepreneurship. Télécom SudParis has 1,000 students, including 700 engineering students and approximately 150 doctoral students. Télécom SudParis is part of the Institut Mines-Télécom, the leading group of engineering schools in France, and shares its campus with Institut Mines-Télécom Business School. Télécom SudParis is a co-founder of the Institut Polytechnique de Paris (IP Paris), a world-class Science and Technology Institute along with École polytechnique, ENSTA Paris, ENSAE Paris, ENPC, and Télécom Paris. Video presentation of Télécom SudParis

About the Institut Mines-Télécom:

The Institut Mines-Télécom (IMT) is a public institution dedicated to higher education and research for innovation in the fields of engineering and digital technology. Constantly attentive to the economic world, IMT combines strong academic and scientific legitimacy, closeness to businesses, and a unique positioning on the major transformations of the 21st century: digital, energy, industrial, and educational. Its activities are deployed within the Mines and Télécom engineering schools under the supervision of the minister in charge of Industry and Electronic Communications, two subsidiaries, and associated or contracted partners. IMT is a founding member of the Alliance Industrie du Futur. It holds dual Carnot certification for the quality of its collaborative research. Video presentation of the Institut Mines-Télécom

Missions

1. Develop generative and representation learning models that integrate mobility flows, transport networks, land use, and socio-demographic data within a common latent space, in order to identify interpretable mobility tensions and evaluate interventions likely to reduce them.

2. Verify the consistency of detected tensions with established indicators of territorial imbalances (mobility-related precariousness, public transport deserts, food deserts, job-housing imbalance).

3. Evaluate the contributions of the method compared to indicators based on a priori definitions (e.g., accessibility thresholds or availability of supply), by identifying latent multifactorial configurations in several data sources.

Activities

• Acquire, clean, align, and combine mobility flows, transport networks, land use data, and socio-demographic data.

• Design data representations and preprocessing pipelines for heterogeneous spatial data sources.

• Implement and train generative and representation learning models.

• Construct vector representations of spatial units and develop methods to extract and interpret latent mobility tensions.

• Analyze the relationships between mobility demand, land use, transport supply, and observed mobility.

• Compare detected tensions with established indicators: mobility-related precariousness, public transport deserts, food deserts, and job-housing imbalance.

• Evaluate complex multifactorial configurations not captured by existing predefined indicators.

• Design and evaluate transport intervention scenarios aimed at reducing detected mobility tensions.

• Program experiments, analyze results, and ensure the reproducibility of the computational pipeline.

• Present and publish results, and collaborate with Mobidec partners as well as with concerned industrial and institutional stakeholders.

Education

• Doctorate obtained or thesis in the process of being completed.

Essential Skills, Knowledge, and Experience

• Excellent skills in mathematical modeling and analysis

• Good programming skills

Desirable Skills, Knowledge, and Experience

• Experience in deep learning and representation learning

• Experience in spatial data science

Capabilities and Aptitudes

• Rigor, project management methodology

• Interpersonal skills with stakeholders at all levels, listening and cooperation spirit

• Ability to work in a team

• Strict adherence to confidentiality obligations regarding the data used

Indicative Remuneration:

• Indicative remuneration range (excluding variable annual bonus): €35,400 - €38,000 gross per year, depending on profile and experience (reduced social charges in the public sector).

Additional Information and Application

• Application deadline: October 16, 2026

• Contract type: 18-month fixed-term contract

• Job category and occupation (internal use): II - P, Postdoctoral Researcher or A (civil service)

• Position open to occupations at the immediately lower level (internal use)

• Job location: Palaiseau (91)

• Positions offered for recruitment are open to all, with, upon request, accommodations for candidates with disabilities

• Job open to civil service employees and/or contract staff

• Working conditions: 44 days of leave, possibility of remote work, restaurant and cafeteria on site, public transport accessibility (with employer contribution) or close to road axes, staff association and sports association on campus

Please submit the following documents. Incomplete applications or those exceeding the indicated limits will be automatically rejected:

• CV (2 pages max).

• A document explaining, in a maximum of 5 lines, why your profile best matches the position, using factual, precise, and non-generic elements.

• A document presenting up to 3 of your best publications. For each: authors, title, publication venue and year; venue ranking (journal: ScimagoJR quartile, SJR and H-index; conference: ERA CORE; if the venue is not ranked, explain why it is high-level); your contribution (2 lines max); and why the publication is important, demonstrates your excellence and/or is related to the postdoctoral topic.

• All grades obtained in Bachelor's (BSc) and Master's (MSc) level courses. Submitting your ranking is optional but constitutes a significant asset.

Contact persons: Associate Professors Vincent Gauthier and Andrea Araldo - -----;