Organisation/Company: CNRS
Department: Laboratoire des sciences du numérique à Nantes
Research Field: Engineering, Computer Science, Mathematics
Researcher Profile: Recognised Researcher (R2)
Country: France
Application Deadline: 26 Jan 2025 - 00:00 (UTC)
Type of Contract: Temporary
Job Status: Full-time
Hours Per Week: 35
Offer Starting Date: 1 Feb 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 The aim of the project is to design objective and rapid procedures for estimating epidemiological indicators, such as the reproduction coefficient R(t) of Covid-19, jointly over several territories, and then to be able to account for the spatio-temporal propagation dynamics.
To this end, propagation models will be developed that take into account not only the underlying epidemic mechanisms, but also the influence of inter-regional exchanges and the errors in reporting the number of new infections, by combining state-of-the-art epidemiological models and graph-based signal processing.
The recruited postdoc researcher will tackle both implementation challenges and theoretical questions related to statistical modeling, prior design in the Bayesian framework, convex and non-convex optimization, and graph signal processing. He/she is expected to develop commented, easy to handle codes to make available the proposed methodologies to nonspecialists. He/she will work in contact with epidemiologists and will be provided real epidemiological data. An interest in interdisciplinary research will be highly appreciated.
The recruited candidate will be hired by the Centre National de la Recherche Scientifique (CNRS) in the framework of ANR grant OptiMoCSI held jointly by LP-IXXI in Lyon, IMT in Toulouse and LS2N in Nantes. CNRS is the largest state-funded French research institution, employing researchers in all fields from exact sciences to humanities. He/she will integrate the Laboratoire des Sciences du Numérique de Nantes (LS2N), in the Signal, Image and Sound (SIMS) team (https://www.ls2n.fr/equipe/sims/) and work on the campus of Centrale Nantes, a top-level engineering school.
Prospective applicants are expected to hold a PhD in signal processing, statistics or a related discipline, excellent programming skills (e.g., in Python or Matlab), and good communication skills in English, both written and oral.
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