Offer Description
La Rochelle Université is recruiting a postdoctoral researcher on a 18 months fixed-term contract.
Employer description
In a higher education and research landscape that has been profoundly reshaped for more than a decade, La Rochelle Université has chosen to structure its research around a thematic by positioning its scientific and academic strengths on societal and environmental issues.
Host Laboratory
Founded in 1993, the Laboratoire Informatique, Image et Interaction (L3i – EA 2118) is the research unit of the Department of Digital Sciences at La Rochelle University. The laboratory brings together 98 members conducting research in the fields of computer science, imaging, and interaction. The Image and Content team has been dedicated to the analysis of visual and video content since the lab's creation and has recently focused on developing artificial intelligence approaches to study marine animal behavior in order to better understand changes in their environment.
Research context
Coastal ecosystems are highly productive and host essential habitats for numerous marine species, including feeding areas, nurseries, breeding grounds, and migratory corridors. The quality of these habitats determines the renewal and dynamics of marine populations and, more broadly, the productivity of coastal ecosystems. However, these ecosystems are increasingly and durably impacted by the cumulative effects of climate change (e.g., rising temperatures, acidification, stratification of the water column) and by expanding human activities in coastal zones (e.g., maritime traffic, fishing, marine aggregate extraction, pollution, and offshore wind farms).
Understanding how marine populations will respond to these rapidly changing environments is therefore essential to support sustainable management and conservation. Yet, predicting population-level responses remains challenging because population dynamics emerge from the individual movements and behaviours of many animals, which are themselves influenced by heterogeneous and changing environmental conditions.
Recent advances in biologging now provide unprecedented opportunities to investigate such processes. Long-term deployments of electronic tags generate large and multimodal datasets describing individual movements and behaviour at sea, including satellite positions, diving profiles, three-dimensional acceleration, oceanographic variables, and physiological parameters. Combined with environmental and anthropogenic data, these observations allow to develop quantitative models linking individual behaviour to environmental conditions.
The postdoctoral position will be part of a 4-year project (DIGIMARINE) that aims to develop a prototype digital twin for coastal marine populations by integrating biologging data, environmental information and artificial intelligence-based movement models. The grey seal (Halichoerus grypus) in the English Channel and the Iroise Sea constitutes the main case study, benefiting from a long-term monitoring program conducted by La Rochelle University.
The first phase of the DIGIMARINE project has focused on the centralisation and harmonisation of biologging, environmental and anthropogenic datasets, as well as on the development and comparison of approaches for simulating individual animal trajectories based on generative AI and state-of-the-art movement models. These foundations now provide an opportunity to move beyond individual-level trajectory predictions and investigate how individual movement processes can be scaled up to the population level.
The postdoctoral researcher will contribute to this next phase by developing quantitative approaches to aggregate individual movement predictions into population-level patterns and by using the resulting modelling framework to explore “what-if” scenarios. These scenarios will investigate how changes in environmental conditions and anthropogenic pressures may affect the spatial distribution and habitat use of marine populations. The objective is to provide a modelling framework able to produce spatially explicit predictions that can contribute to future decision-support tools for marine management and conservation (digital twin).
Job description
The postdoctoral researcher will contribute to the development of the digital twin by focusing on the transition from individual movement predictions to population-level dynamics and the exploration of future environmental and anthropogenic scenarios. Building on the individual trajectory simulation framework developed during the first phase of the project, the researcher will:
- Scale up individual movement predictions to population level
Develop quantitative and statistical approaches to aggregate simulated individual trajectories and infer population-level patterns of movement and habitat use. The researcher will investigate how individual variability, behavioural strategies and environmental responses combine to generate emergent spatial and temporal patterns at the population level. Particular attention will be given to the validation of population-level predictions against observed biologging data and independent information on grey seal distribution.
- Develop and assess what-if scenarios
Use the population-level modelling framework to simulate alternative environmental and anthropogenic conditions. Scenarios may include changes in oceanographic conditions associated with climate change, as well as modifications of anthropogenic pressures such as maritime traffic or fisheries. The researcher will quantify how these changes may affect the spatial distribution, habitat use and potential exposure of the population to different pressures, and identify conditions under which substantial changes in population-level patterns may occur.
- Contribute to the development of a spatial decision-support system
Translate population-level predictions and scenario results into spatially explicit indicators of habitat use, exposure and potential risk. Depending on the progress of the project, these outputs may be integrated into the UCLR platform (Urban Coastal Lab La Rochelle) to facilitate the visualization and exploration of alternative scenarios. The researcher may also contribute to the development of indicators that could support the prioritisation of areas for management and conservation. Part of this work may be conducted in collaboration with a Master's student to facilitate visualization of habitats under different scenarios.
The postdoctoral researcher will contribute to the scientific valorisation of the results through publications in international peer-reviewed journals and presentations at scientific conferences. Supervision will be provided by Dr. Marine Gonse and Dr. Mickael Coustaty (L3i). Interactions are also planned with Dr. Cécile Vincent (Pelagis Observatory), an expert in grey seal tagging and telemetry.
Requirements
Skills required
The candidate must hold a PhD in quantitative ecology, movement ecology, ecological modelling, biostatistics or a closely related field. The ideal candidate will have experience in analysing animal movement data and/or developing quantitative models of ecological processes, with an interest in artificial intelligence and machine learning approaches. The candidate should demonstrate the ability to conduct independent research and to work at the interface between marine ecology, quantitative modelling and computer science.
Technical Skills:
- Strong background in quantitative ecology, ecological modelling, movement ecology and/or population dynamics
- Experience with the analysis and modelling of spatiotemporal ecological data
- Experience with individual-based models, movement models, simulation approaches or other methods for linking individual processes to population-level patterns
- Experience with artificial intelligence or deep learning approaches is desirable, but expertise in a specific AI method is not required
- Strong programming skills in Python and R, with the ability to develop reproducible and well-documented analytical workflows
- Experience with spatial data analysis and geospatial modelling
- Experience with biologging, telemetry or other animal movement datasets
- Interest in digital twin approaches and scenario-based modelling
Operational Skills:
- Rigor, autonomy, and initiative
- Ability to work in a multidisciplinary team involving ecologists, biologists and computer scientists
- Strong organizational and time-management skills
- Communication skills for diverse audiences
- Critical thinking and curiosity
- Project management and activity planning
- Reporting progress through concise written summaries
- Strong writing and oral presentation skills in English
- Proficiency in English (reading, writing and speaking). French is desirable but not mandatory.
Education Level: PhD or equivalent
Additional Information
Benefits
Type of recruitment
- Category: A
- Placement: Laboratoire Informatique, Image et Interaction (L3i – EA 2118)
- Recruitment: Fixed-term, 18 months
- Working hours: full-time
- Remuneration: From €2069€ gross/month, in accordance with La Rochelle University's contractual personnel management framework.
If the candidate obtained his/her doctorate less than three years ago, a postdoctoral contract may be offered. After 3 years, an equivalent contract will be offered.
Recruitment open to anyone with a RQTH (Qualified Health and Disability certificate).
Benefits
- 75% contribution to home-to-work public transport costs
- Sustainable mobility package for the use of a cycle/carpool for home-work journeys.
- Mutuelle participation
- Telecommuting possible for up to 2 days a week
- Collective catering on the university campus
- Sport, leisure and cultural activities for all employees
Selection process
How to apply?
Your application must include the following documents. Please submit your application (job reference: RECH/L3i/26-19) before the 9th October 2025.
- cover letter
- detailed curriculum vitae
- copy of highest diploma
You can send your application by email to marine.gonse@univ-lr.fr before the 31st October 2025.
Work Location(s)
- Number of offers available: 1
- Company/Institute: La Rochelle Université
- Country: France
- State/Province: Nouvelle Aquitaine
- City: LA ROCHELLE
- Postal Code: 17000
- Street: 21 avenue Albert Einstein
Contact
- City: La Rochelle
- Website: https://www.univ-larochelle.fr
- Street: 23 avenue Albert Einstein, BP 33060
- Postal Code: 17031
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