88 machine-learning-"https:"-"https:"-"https:" "Computer Vision Center" positions at EPFL
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drug-discovery and biomedical sciences. We are looking for candidates with A PhD in machine learning, computer science, computational biology, or a closely related field (completed or near completion
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Quantitative Finance at EPFL seeks postdocs to reinforce our research in quantitative finance with a focus on applied machine learning. Main duties and responsibilities Working and collaborating on research
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towards impact in early drug discovery through public and Novartis-internal datasets. We are looking for candidates with A PhD in machine learning, computer science, computational biology, or a
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modelling satellite imagery and textual conflict data. Advances in vision-language representation learning will be explored to link the two sources of information through alignment pipelines, localisation
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. Specific areas of interest include, but are not limited to, molecular simulations, electronic structure theory, thermodynamic modeling, machine-learning and artificial intelligence based methods, with
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research and teaching in key computing areas, including High-Performance Computing (HPC), Artificial Intelligence and Machine Learning (AI/ML), scientific computing, trusted research environments
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, machine learning, or an equivalent field; recent graduates are welcome Strong Python skills and the ability to write clean, modular, tested, and documented code Hands-on experience with graph data
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background, and an outstanding MSc degree in Engineering, Computer Science, Physics, Applied Mathematics, or a related field. You should be proficient in or willing to learn generative deep learning – in
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biology, physics, computer science, and engineering. For more information about the Dubochet Center please visit our website: https://dci-lausanne.ch/ . Informations Only applications submitted through
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machine learning. The project focuses on the discovery of governing equations and constitutive relations for key multiphysics phenomena on the basis of rich micromechanical and experimental data. It pushes