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degree in physics, mathematics or any related field; correspondingly, Postdocs hold a PhD or equivalent degree in the above mentioned fields. What we offer State of the art on-site high performance/GPU
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-of-the-art compute and GPU infrastructure, including H100 and B300 GPU clusters. Innovation: The opportunity to apply a recently published, "proof-of-concept" method for synthetic enhancer design to a critical
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(static and dynamic photochemistry, heterogeneous catalysis, modeling of interfaces and ionic liquids). It benefits from access to the CBPSMN mesocenter, with a large amount CPUs and GPUs facilities. In
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Max Planck Institute for Multidisciplinary Sciences, Göttingen | Gottingen, Niedersachsen | Germany | 23 days ago
. What we offer State of the art on-site high performance/GPU compute facilities Competitive research in an inspiring, world-class environment A wide range of offers to help you balance work and family
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%). You will work on the extension of the DUNE-FEM package to support computations on GPU hardware with various types of Finite Element methods. This work is embedded in a research project considering
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. Demonstrated experience developing and running computational tools for high-performance computing environment, including distributed parallelism for GPUs. Demonstrated experience in common scientific programming
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construction of a new dataset from Subaru Hyper Suprime-Cam (HSC) and N-body simulations and science projects using those datasets. In addition, the successful candidate will be required to maintain a new GPU
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with excellent facilities for protein science research. There will be direct access to advanced biophysical infrastructure in the biophysics core facility headed by the PI, a GPU cluster with working
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and writing scientific code - Knowledge of at least one of the parallel programming paradigms (MPI, OpenMP, GPU) - Proficiency in both spoken and written English is essential (work will be carried out
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algorithms. The post-doc will carry out theoretical work on causal abstraction and causal alignment, implement algorithms and experimental pipelines in Python/PyTorch, and run experiments on GPU clusters