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and planet formation context Experience in the field with HPC system usage and parallel/distributed computing Knowledge in GPU-based programming would be considered an asset Proven record in publication
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computing, domain-specific multi- and manycore architectures, networks-on-chip (NoCs), methods and algorithms for application parallelization, simulators and virtual platforms for application- and
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times through higher parallelization and enable targeted stimulation of hardware faults by adjusting the models. To this end, a simulation environment based on a virtual prototype will be developed using
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. The field has emerged in parallel with rapid technological improvements in computing, the spread of Internet and mobile technologies, and the increased digitalization of data and of people’s lives. Our group
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Max Planck Institute for Demographic Research (MPIDR) | Rostock, Mecklenburg Vorpommern | Germany | about 19 hours ago
domains of population research by combining the methods and perspectives of computational sciences, social and behavioral sciences, and statistics. The field has emerged in parallel with rapid technological
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Max Planck Institute for Demographic Research, Rostock | Rostock, Mecklenburg Vorpommern | Germany | 17 days ago
, social and behavioral sciences, and statistics. The field has emerged in parallel with rapid technological improvements in computing, the spread of Internet and mobile technologies, and the increased
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using the programming language Fortran. Experience or willingness to run numerical models on parallelized supercomputers. Experience in the analysis of model output using Python or a similar high-level
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Identify new applications for Machine Learning in science, engineering, and technology Develop, implement and refine ML techniques Implement parallel ML training on the High Performance Computers Engage in
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and/or Matlab, parallel programming Experience in international collaboration Fluent in English (spoken and written) Demonstrated ability to publish in international journals and present at conferences
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- into a GPU-enabled and parallel code to run efficiently on state-of-the-art exascale hardware Designing implementations and reviewing community contributions of library features and new statistical