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Field
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EU MSCA doctoral (PhD) position in Materials Engineering with focus on computational optimization of
MSCA doctoral (PhD) position in Materials Engineering with focus on computational optimization of additively manufactured Mg alloys for biodegradable implant applications. Host: Helmholtz-Zentrum Hereon
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III of the Call for Proposals - Demonstrable experience in tasks related to multibody systems dynamics, particularly slack modelling and data fusion algorithms with computational models. - Candidates
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III of the Call for Proposals. - Demonstrable experience in tasks related to multibody systems dynamics, particularly slack modeling and data fusion algorithms with computational models. - Candidates
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Exactly: A Bayesian Approach. The project aims to address the challenges in pooling inference, by developing and implementing either exact or asymptotically exact Monte Carlo algorithms in collaboration
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, machine learning or similar. Alternatively, you have gained essentially corresponding knowledge in another way. The applicant is expected to have good knowledge of computer science, mathematics, algorithms
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, with both academia and industry recognising its importance. Distribution is an integral part of innumerous computer systems, providing them with essential improvements to aspects such as performance and
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28 Aug 2025 Job Information Organisation/Company CNRS Department Laboratoire d'informatique de modélisation et d'optimisation des systèmes Research Field Computer science Mathematics » Algorithms
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diverse team of PhD candidates who will focus on three key areas: Probabilistic and differentiable algorithms for machine learning; Programming language implementation for high performance computing
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algorithms to compute similarity between interaction interfaces across millions of comparisons. This hinders identification of novel modes of protein binding, i.e. those predicted by AlphaFold, and it hinders
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Status Full-time Is the job funded through the EU Research Framework Programme? Horizon Europe - MSCA Reference Number 2023-DN-01 Marie Curie Grant Agreement Number 101169044 Is the Job related to staff