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learning, epigenomic data, and mechanistic modelling. The mission is to contribute to the development of predictive models of the replication initiation probability landscape (IPLS) from limited experimental
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research tasks, using both analytical and numerical methods, contributing to numerical validation of analytical predictions where relevant; (b) write up results for publication and present them at group
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use numerical models to interpret and predict mechanical behavior. - Carry out a cross-analysis of experimental, microstructural, and numerical results. - Disseminate scientific results (publications
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predictive models of immune responses. Develop advanced and innovative machine learning methodologies and analyze data. The postdoctoral researcher will join the groups of T. Mora and A. Walczak, whose
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generation, targeted atomistic simulations, structural descriptor extraction, and predictive models. The work will aim to establish links between local pore geometry, structural disorder, sodium adsorption
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microscopy, depending on the candidate's expertise; - analyse quantitative biochemical, biophysical, imaging, and cellular data; - integrate experimental findings with computational predictions generated
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the growth of carbon chains. • Collaborate with astrochemists and observers to validate theoretical predictions. This position will focus on modeling dust production in supernova explosions, a key process for
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bachelor's students and ensuring the proper maintenance and operation of the synthesis lab in accordance with the recommendations provided by funding agencies and the laboratory administration. • Develop
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of instrumentation: - Define measurement protocols (PIT-tags, hydrophones, geophones, sediment traps, piezometric probes): full responsibility. - Supervise site equipment and device maintenance: primary responsibility
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, the cell cycle, and the maintenance of genetic stability. This position is ideal for a recent Ph.D. graduate with expertise in cell biology or cancer biology. The position is set within a multidisciplinary