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with leading machine learning frameworks and modern AI environments, including multi-GPU model training and large-scale inference on dozens to hundreds GPUs, are required. Additional Qualifications
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. transformer models). One focus of this work will be on B-cell receptor evolution. Experience in applications of modern machine learning methods as well as in biological data analysis are needed for the position
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machine learning methods for computational materials physics and chemistry. Projects include: The aim is to develop generalized equivariant neural network models NequIP and Allegro for machine learned
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and Machine Learning, with a focus on studying geometric structures in data and models and how to leverage such structure for the design of efficient machine learning algorithms with provable guarantees
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machine learning methods as well as in biological data analysis are needed for the position. The postdoctoral researcher will play a leading role in this research, including methods development, data
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reproducible analysis workflows Familiarity with computational models of vision and machine learning methods (for example CNNs, deep generative models, encoding models) is preferred but not required Ability
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computational models of vision and machine learning methods (for example CNNs, deep generative models, encoding models) is preferred but not required Ability to communicate scientific results clearly through
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to have a strong background in the foundations of machine learning. Special Instructions Required application documents include a cover letter, CV, a statement of research interests, and up to three
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Details Title Postdoctoral Fellow – PKPD Modelling, Lung-on-Chip School Wyss Institute for Biologically Inspired Engineering Department/Area Position Description About the Wyss: The Wyss Institute’s
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to) statistical modeling in protein folding, neurobiology, role of synthetic data in statistical analysis, machine learning and AI methods, causal inference in biomedical data. The appointment will be for up