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), whose objective is to extend the HLA-Epicheck model, originally developed within the framework of a PhD thesis, and to implement new deep learning approaches to assess donor–recipient compatibility in
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Postdoctoral researcher in the analysis of single-cell and spatial transcriptomics experiments (M/F)
engineeringYears of Research Experience1 - 4 Additional Information Eligibility criteria - Holder of a PhD in a field related to cancer and treatment resistance - Conducting and analyzing single-cell and spatial
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Additional Information Eligibility criteria • PhD in developmental biology, or related fields such as regenerative biology, cell biology, molecular genetics • Experience in microscopy (preferably live
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Additional Information Eligibility criteria ● A relevant PhD degree in semiconductor physics, material sciences, or similar. ● Hands-on experience with III-V semiconductor deposition processes (e.g. MOCVD, MBE
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LanguagesFRENCHLevelBasic Research FieldChemistryYears of Research ExperienceNone Research FieldPhysicsYears of Research ExperienceNone Additional Information Eligibility criteria Holder of PhD in chemistry, the candidate
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Eligibility criteria PhD in Mathematics. Candidates with expertise in one of the following research areas are encouraged to apply: - Complex foliations; - Birational geometry; - Qualitative theory of real
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Additional Information Eligibility criteria The candidate should have a PhD in Biology/Evolutionary Biology and skills in bioinformatics and macroevolution (ideally models of phenotypic evolution
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FieldMathematicsYears of Research Experience1 - 4 Research FieldHistory » History of scienceYears of Research Experience1 - 4 Additional Information Eligibility criteria - PhD in computer science or applied mathematics
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Experience1 - 4 Additional Information Eligibility criteria The position requires a PhD in Earth sciences, applied mathematics, or a related field, experience with topological analysis or data science, and
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scienceEducation LevelPhD or equivalent Skills/Qualifications PhD in computer science Background in probability, Markov chains, MDPs Knowledge about reinforcement learning and planning are a plus but not necessary