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well as make recommendations Ability to work with mathematical concepts and basic methods for research and statistical analysis Ability to take initiative and independently plan, organize, coordinate, and
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, multilevel analysis). Knowledge in developing predictive and forecasting models in health or environmental research. Skills in machine learning or AI techniques for prediction of complex outcomes. Experience
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2 Mar 2026 Job Information Organisation/Company Ecole Centrale de Lyon Research Field Mathematics Engineering Researcher Profile First Stage Researcher (R1) Positions Master Positions Application
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synaptic resilience and the reliability of synaptic responses. The work primarily involves mathematical modeling and numerical simulation, but also the analysis of experimental datasets for model validation
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. The focus is on the development of original mathematical methods for AI and its applications aimed at the modelling and analysis of complex phenomena particularly within economics and finance, energy finance
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correspondence, memorandums, report narratives, research summaries, procedure manuals, surveys, grant application data, and other materials Performs complex data analysis Makes special and regular reports and
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Econometrics (particularly applied micro, behavioural, or decision-focused modelling) Applied Mathematics, Operations Research, or Statistics Systems Engineering, Decision Science, or Complex Systems
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» Algebra Mathematics » Applied mathematics Mathematics » Computational mathematics Mathematics » Mathematical analysis Mathematics » Number theory Mathematics » Probability theory Mathematics » Statistics
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. The successful candidate will engage in innovative research addressing statistical methodology, machine learning, and/or learning techniques in complex biomedical and health-related challenges. We particularly
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particular, we aim to develop a neural network architecture that will allow us to accelerate solving AC power flow (AC‑PF) computations, potentially facilitating real‑time contingency analysis, rapid design