PhD student fixed-term contract (M/F) in possibilistic ecosystem modelling applied to human evo[...]

European Commission; France; Sur place; EUR 40 000 - 60 000; Plein temps

Résumé du poste

Une opportunité de thèse est proposée au Centre Européen de Recherche et d'Enseignement des Géosciences de l'Environnement pour étudier la contigence de l'évolution humaine à travers des approches de modélisation possibiliste. Le doctorant sera impliqué dans un projet interdisciplinaire, collaborant avec divers experts pour formaliser des données sur les paléoécosystèmes et explorer des scénarios évolutifs alternatifs.

Qualifications

• Connaissance des systèmes écologiques et de la paléoécologie.
• Compétences en modélisation, y compris l'EDEN et les approches possibilistes.
• Capacité à collaborer avec une communauté de chercheurs diversifiée.

Responsabilités

• Compiler des connaissances expertes sur les paléoécosystèmes.
• Développer un modèle possibiliste pour explorer des scénarios évolutifs.
• Analyser les trajectoires de l'évolution humaine en fonction des données écologiques.

Connaissances

Modélisation

Recherche interdisciplinaire

Analyse écologique

Formation

Master en sciences environnementales ou disciplines connexes

Description du poste

Organisation/Company CNRS Department Centre de Recherche et d'Enseignement des Géosciences de l'Environnement Research Field History Anthropology Environmental science Researcher Profile First Stage Researcher (R1) Country France Application Deadline 24 Jun 2025 - 23:59 (UTC) Type of Contract Temporary Job Status Full-time Hours Per Week 35 Offer Starting Date 1 Oct 2025 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

This thesis work will be carried out as part of the 80PRIME ALEA project funded by the CNRS Mission for Transversal and Interdisciplinary Initiatives (MITI).

The PhD student will be based at the Centre Européen de Recherche et d'Enseignement des Géosciences de l'Environnement (CEREGE) in Aix en Provence, France. He/she will be assigned to the CLIMAT team. See https://www.cerege.fr for details of the host laboratory.

To formalise the expert knowledge, it will be necessary to work with the researchers directly involved in the ALEA project (in Paris, Bordeaux, Poitiers, Montpellier) and with those of the interdisciplinary research group of the GDR RIFT.

The doctoral student will be co-supervised by a thesis director and a co-director who respect gender and cultural diversity. A thesis committee will meet at least once a year to monitor the progress of the thesis project and the student's professional project.

How did the genus Homo converge towards a single representative, when the fossil record of the human branch indicates a plurality of species for more than three million years? The differences in the adaptive trajectories of Homo and paranthropes, the other hominins that became extinct just over a million years ago, are undoubtedly the result of multiple and diverse interactions of a set of mechanisms that need to be considered in their full ecosystemic context. However, to date, no team or model, whether deterministic (based on differential equations) or probabilistic (frequentist, Bayesian, etc.), is capable of taking an integrated view of the impact on human evolution of mechanisms such as intra- and interspecific competition, differentiation of ecological niches and in particular diets, diversification of behaviour or the emergence of cognitive and cultural differences. Similarly, these models do not allow us to study the impact of volcanism or climatic fluctuations on the evolution of species, even though they have a direct influence on the distribution and availability of biotic and abiotic resources (type, quality, diversity, spatio-temporal accessibility), both regionally and globally.

So, while many factors may have influenced human evolution, we wonder whether trajectories other than the one observed (a priori contingent) would have been possible. Although this trajectory cannot be 'replayed', it is possible to test this hypothesis using a possibilistic modelling approach, which allows the known causal factors behind this evolution to be taken into account or not.

Possibilistic models of the EDEN type, which are used to study the histories of present-day socio-ecosystems, are well suited to this problem, as they are qualitative and accommodate knowledge and data of contrasting natures (e.g. physico-chemical, climato-hydrological, bio-ecological, etc.) and unevenly distributed in time and space, such as the partial data from palaeontological and archaeological records.

The aim of this thesis project is to attempt to answer the question of the contingent nature (or not) of human evolution, by assembling as much expert knowledge as possible on palaeoecosystems from several scientific disciplines. Our models will not be able to test the contingency of the Homo genus, but a contingency, one that would exhibit different trajectories based on a set of mechanisms and their interactions, possibly played out in a different order, or not played out at all.

More specifically, the aims of the thesis are 1) to compile this contrasting expert knowledge on palaeoecosystems, 2) to formalise this knowledge within a possibilistic model, using the EDEN (Ecological Discrete Event Network) formalism, and 3) to explore alternative (contingent) evolutionary scenarios of the Homo genus system and its associated ecosystems between 4 and 1 Ma. This will be done by analysing the various trajectories calculated by the model and dependent on climate, palaeoecology, niche partitions, material cultures, etc.
The formalisation of expert knowledge (objective 1) will be based on (i) exchanges with a multidisciplinary community already made up of archaeologists, palaeontologists, palaeoclimatologists, geologists, etc. whose fields of study are the fossiliferous sites of Pliocene and Lower Pleistocene East Africa. These exchanges will be supplemented by (ii) data from the literature and (iii) technical constraints linked to the design of possibilistic models. The development of the model (objective 2) and the exploration of evolutionary scenarios (objective 3) will be carried out on a Jupyter platform and with models that are already available.