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experiments. The objective is to develop Bayesian causal models and neural networks capable of identifying relevant causal relationships between instrumental parameters and observed anomalies. The work will
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related field, with a strong focus on optimization. Technical Skills Proficiency in programming, preferably in Python or a similar language commonly used in optimization. Familiarity with mathematical
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that couples high‑performance computing with instrumental platforms integrated in the UPPA‑Tech network. Five platforms are directly supported by IPREM: POLYCaTS (polymer analysis and characterisation
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and programming skills (Python preferred). Excellent written and verbal communication in English. Passion for exploring the frontiers of condensed matter physics. What We Offer · Pioneering
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contribute to the development of a proof of concept obtained at University Côte d’Azur for accessing the content of a metabolomics knowledge graph (KG) with a large language model. It is Python prototype of a
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. Metodi Metodiev (project PI) and will benefit from access to state-of-the-art technological platforms and our network of gene therapy experts.Main missions: •Histological (IF, activity assays) analysis
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, from new comprehensive community surveillance system RELAB, iv) studying and modelling the dynamics of antibodies following mosquito bites and exploring implications for the monitoring of mosquito born
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Independent supervision of students and doctoral candidates Support in the further development of the Bachelor en Formation Pédagogique program and in the expansion of networks with stakeholders and partners
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Responsibilities: Ensure communication with internal and external stakeholders Organize and prepare content/analysis for project events, such as stakeholder meetings and policy briefs Network with researchers and
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metabolism in rare and more common neurodegenerative or neurometabolic diseases. We exploit genomic and post-genomic data to fill gaps in metabolic networks, discover new enzyme functions, and elucidate