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, etc.) o Energetic frustration or protein energy landscape analysis o Machine learning in protein science o +2 years of experience after PhD Knowledge of evolutionary biology concepts (phylogenetics
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performance with classical methods. Qualifications PhD in Physics, Computer Science, Applied Mathematics, or related fields. Strong background in at least one of the following: machine learning, quantum
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an extensive representation of domestic varieties, landraces and crop wild relatives. The candidate will be in charge of: - Analysing SV in the pangenome of Brassica that are close to genes and may have been
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: Education: PhD in Biomedical, Neuroengineering, Electronic or Electrical Engineering, Physics, Bioinformatics or related engineering fields · Advanced Python / MATLAB programming skills. · Electrophysiology
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expertise in machine learning or computational modelling who are eager to advance conceptual innovation toward practical industrial deployment. Qualifications PhD in Computer Science, Machine Learning