Postdoctoral Position M/F in Statistical Analysis of Species Interactions Using Camera Traps

Job Description

Missions

Camera traps are increasingly used to study interspecific interactions, particularly through the analysis of proximal co-occurrence—i.e., the conditional probability that one species appears after another within a given time interval. These interspecific interactions can influence species' activity and movement patterns, as they may avoid or attract each other through spatial and/or temporal behavioral responses. Intraspecific interactions may also occur, with individuals either avoiding one another or moving together. However, suitable statistical techniques for analyzing such data remain underdeveloped. Point processes offer a promising approach for studying short-term interspecific interactions using camera trap data. In particular, the multivariate Hawkes process (Nicvert et al., 2024) emerges as a suitable theoretical framework for unraveling the complexity of interactions that structure ecological communities.

The postdoctoral researcher will focus on studying short-term interspecific interactions (on the scale of hours) by developing or adapting statistical methods and handling large datasets.

Activity

The main objective will be to model how detection probability changes given the prior passage of another species a certain time earlier, using statistical methods tailored to point processes.
The work will involve:
- Familiarizing oneself with statistical methods for point processes;
- Improving existing methods to incorporate a detection rate that varies over time and space;
- Accounting for trap/environment effects (e.g., traps located in open areas or other environmental variables);
- Potentially extending the model to include the circadian rhythms of the different species whose detection is being modeled, thereby allowing the detection rate to depend on the time of day.

The postdoctoral researcher will have access to large, pre-existing datasets covering multiple sectors of the French Alps, providing a solid foundation for testing and validating the proposed models.

Occasional fieldwork may be required.

Your Profil

Skills

Holder of a PhD in ecology, mathematics, or computer science:
- Strong experience in statistical ecology and/or statistics;
- Programming skills in R and/or Python;
- Interest in ecological and conservation issues;
- Interest in mountain environments.

Your Work Environment

The Laboratoire d'Écologie Alpine (LECA) is a joint research unit of the CNRS, Université Grenoble Alpes, and Université Savoie Mont-Blanc. The team based on the Chambéry campus is nationally renowned for its expertise in the study of mountain large mammals, as well as for its statistical and modeling expertise. It maintains constant collaboration with field practitioners, parks, reserves, and biodiversity monitoring organizations in the Alpine region.

The postdoctoral researcher will benefit from a diverse and dynamic environment, fostering numerous interactions. Collaborations with statistician colleagues are also planned.

Compensation and benefits

Compensation

From €3,041 gross/month, based on experience and CNRS pay scale

Annual leave and RTT

44 jours

Remote Working practice and compensation

Pratique et indemnisation du TT

Transport

Prise en charge à 75% du coût et forfait mobilité durable jusqu’à 300€

About the offer

About the CNRS

The CNRS is a major player in fundamental research on a global scale. The CNRS is the only French organization active in all scientific fields. Its unique position as a multi-specialist allows it to bring together different disciplines to address the most important challenges of the contemporary world, in connection with the actors of change.

CNRS

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