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methods for single-cell data analysis (tools developed by the team : https://github.com/cantinilab ). Single-cell high-throughput sequencing, extracting huge amounts molecular data from a cell, is creating
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(FSTM) at the University of Luxembourg contributes multidisciplinary expertise in the fields of Mathematics, Physics, Engineering, Computer Science, Life Sciences and Medicine. Through its dual mission
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Artificial Intelligence (applied mathematics, computer science, etc.), or a thesis defense scheduled for 2025. • Research contributions in deep learning, statistical learning, natural language processing (NLP
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, Applied Mathematics, or a related field. Strong foundation in computational modelling & numerical simulations The laboratory The Decision and Bayesian Computation (DBC) – Epiméthée (EPI) laboratory
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-pressure hydrogen synthesis will be explored to extend the accessible range of hydrogen content. The key expected outcome of this work is a deeper understanding of the role of hydrogen in the complex
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health tools. Basic proficiency in data analysis (Python or R); experience with speech analysis libraries or NLP is an asset. Strong scientific writing skills and a collaborative spirit. High motivation
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(FSTM) at the University of Luxembourg contributes multidisciplinary expertise in the fields of Mathematics, Physics, Engineering, Computer Science, Life Sciences and Medicine. Through its dual mission
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(FSTM) at the University of Luxembourg contributes multidisciplinary expertise in the fields of Mathematics, Physics, Engineering, Computer Science, Life Sciences and Medicine. Through its dual mission
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closely with bioinformaticians, immunologists, and diabetologists to ensure integrated analysis and interpretation; Prepare scientific manuscripts for publication and present findings at national and
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more (for an overview of these technologies, see http://behaverse.org/ ). Your role in this team will be to develop computational models and data analysis code to process large, multimodal behavioral