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Field
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therapies for the treatment of corneal diseases. One research program investigates the microenvironment/niche of human limbal stem cells to elucidate those factors that govern the fate of limbal stem cells
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, molecular biotechnology and computational sciences. The modern Campus harbors the buildings of the science faculties and institutes, in direct vicinity to the University Hospital Heidelberg, the Max Planck
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. Among the methods used are high-throughput CRISPR screening, protein deep mutational scanning, massively parallel reporter assays, and genetic manipulation of cell lines and mice. The successful candidate
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Post-doctorate position (M/F) : Exascale Port of a 3D Sparse PIC Simulation Code for Plasma Modeling
-Saclay and Université Versailles Saint-Quentin. It specializes in high performance computing and numerical simulations in close connection with physical applications, parallel software engineering
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in a dynamic and collaborative team. In collaboration with the Edinburgh Parallel Computing Centre (EPCC) and our industry partners, the focus of the role is the development of a new solver for
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applications. You will be hosted in the Sustainable Electronic Technologies group in the Electronics and computer science through which the Novel and Compound facilities are managed. The expertise of the team
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on finding and cultivating talented people who are passionate about what they do. Join us and be a part of the diverse Caltech community. Job Summary The Research Assistant in Scientific Computing will work
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epilepsy patients and non-human primates are conducted using identical behavioral paradigms and combined with computational approaches. We are seeking an extremely motivated postdoctoral researcher with
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. Knowledge of multi-dimensional code development (in C++/C/Fortran) for two-phase/multiphase flow and turbulent combustion applications, and parallel scientific computing. Experience in geometry manipulation
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-edge Machine Learning applications on the Exascale computer JUPITER. Your work will include: Developing, implementing, and refining ML techniques suited for the largest scale Parallelizing model training