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Eligibility criteria Selection will be based on the following scientific and technical criteria: • PhD in computational biology, machine learning, bioinformatics or a related field. • Proficiency with Python
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) / InP contact layer (200 nm) / Si substrate The objective of the project is to develop a plasma etching process for this multilayer stack, enabling selective etch stopping on the InP contact layer, which
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in the framework of the BBEST PEPR. The project aims to valorise syngas derived from biomass via the OX-ZEO process. This relay catalytic process combines a hydrogenating metal oxide to produce
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mixtures, including information retrieval, random access, approximate search, querying and filtering, encryption, compression, and many other information-processing tasks. Our team is looking for a talented
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-VIS-NIR). Experience in hyperspectral data processing (HMSPL, μXRF, μXAS) and statistical analysis (clustering, machine learning) is preferred. Familiarity with fossilization processes and taphonomic
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investigate out-of-equilibrium dynamics in high-dimensional disordered systems (including models relevant to machine learning and optimization) by characterizing the fixed points (metastable states, attractors
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, integrating statistical inference, machine learning, and population genetics. We will develop advanced computational methods to characterize the functioning of T- and B-cell repertoires. The goal is to build
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astrophysics, cosmology, or a related field completed by the start date; strong programming skills; working knowledge of machine learning applied to astrophysics and cosmology, in particular simulation-based
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present scientific results. # Software and tools - Proficiency in standard computer tools. - Experience with mass spectrometry data processing and analysis software. # Personal skills - Autonomy, rigor, and
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of Research Experience1 - 4 Additional Information Eligibility criteria We are looking for a doctor in particle physics with less than two years of experience after the PhD. Experience in machine learning and