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motivated computational Postdoctoral Research Assistant to lead on an established and successful research line aimed at understanding the role of the tumour immune microenvironment (TIME) in response
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them on massively parallel computers ? CPU, GPU, and APU systems. The successful candidate will work with Prof. Uri Shumlak and Prof. Jingwei Hu and contribute to a project that combines novel low-rank
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sets and backgrounds are therefore also critical. Additional desired skills include the following: experience using ROMS; familiarity with parallel computing and high-performance computing environments
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13 Feb 2025 Job Information Organisation/Company Télécom Paris Research Field Computer science » Other Researcher Profile Recognised Researcher (R2) Positions Postdoc Positions Country France
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mouse models and a specific battery of cognitive tests will be studied in parallel with human clinical cohorts. Responsibilities With the ultimate goal of creating a harmonized battery, one position will
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Helmholtz-Zentrum Potsdam - Deutsches GeoForschungsZentrum GFZ | Potsdam, Brandenburg | Germany | 2 months ago
Demonstrated excellent programming skills in C++ and FORTRAN and editing source codes written in these languages Familiarity with computational techniques of high performance massive parallel computing in Linux
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#, FORTRAN, Perl, Python) as well as parallel computing; Ability to work effectively in a team environment with a multidisciplinary group of scientists Ability to conduct research with limited supervision Good
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will be conducted primarily at the UHF of 10.5 Tesla (10.5T) with advanced capabilities (including 16-channel parallel transmit (pTx), 128-channel receive, and high-performance gradient coils
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, Statistical Physics, Genome Annotation, and/or related fields Practical experience with High Performance Computing Systems as well as parallel/distributed programming Very good command of written and spoken
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order to expedite the simulation, MagTense is based on a core implemented in the Fortran programming language, and it relies on the platform CUDA for parallelization of the computation over several GPUs