12 evolution-"https:"-"https:"-"https:"-"UNIVERSITY-OF-LUXEMBOURG" positions at Nature Careers in France
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in their decisions and businesses in their strategies. Do you want to know more about LIST? Check our website: https://www.list.lu/ How will you contribute? You will be contributing to the BESSER
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and educational issues with the common goal of contributing to an inclusive, open and resourceful society. Your role The Research and Development Specialist will be a member of the Department
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and lead their own research team within a research structure in France affilated with Inserm or CNRS, and Université Paris-Cité. o It also aims to encourage the development of high-quality, mid-term
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Cardioembolic Stroke Risk Stratification using AI Accelerated Patient-Specific Blood Flow Simulation
. These approaches allow for precise simulations of fluid mechanics applied to physiological processes, contributing to a better understanding of diseases and the development of innovative medical technologies
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group “development of mobile agro-environmental sensing” within the IAT and advance the research in this domain with particular emphasis on research in the five IAT living labs. A central aspect of your
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for brain disorders and many hospital clinicians are also investigators of the Institute. As part of its scientific strategy development plan, the Paris Brain Institute has recently launched an ambitious
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often struggle with domain shift, limited generalization, and the gap between simulation and deployment. These challenges motivate the development of advanced spatio-temporal learning frameworks that can
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domains, fostering the acquisition of horizontal skills around presentation & communication skills, scientific English, protocol development, data evaluation, and training in Nutrition. A close link to lab
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projects on the molecular and cellular mechanisms of infectious and chronic inflammatory diseases with the aim to apply this knowledge to the development of improved diagnostics, vaccines and therapeutics
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. Côte d’Azur & INRIA), will be focused on the development and the understanding of deep latent variables models for unsupervised learning with massive heterogenous data. Although deep learning methods and