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computing Experience in the development and application of process-based models and/or model–data fusion and data assimilation methods Very good programming skills in Python and/or Fortran; knowledge of
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and parallel computing, or scientific simulation; Effective oral and written communication skills; Ability to work well independently as well as in a collaborative team environment. COMPENSATION AND
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Physics, specializing in neutronics or nuclear engineering Computing skills: Proficiency in C++ (as the core computational kernels are written in this language) Applied mathematics skills: Numerical
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cyclones, the Madden–Julian Oscillation, and atmospheric rivers. We combine theory, observations, a hierarchy of numerical models, and machine-learning methods to understand their formation, dynamics
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Skip to content Postdoctoral Research Associate in Computational Modelling for Cardiovascular Digital Twins Opportunity ID 11265 Faculty University Research Institute Location QM London
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Scientific Employee (f/m/d) on the 'HPC-RSE-Nexus' project / Completed university studies (Master...
years) in the specified area # Experience in the field of high-performance computing # In-depth knowledge of Linux server administration, HPC, and parallel storage systems # Knowledge of using and
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The Department of Chemistry, Section for Chemical Biology invites applicants for a PhD fellowship in chemical methods for half-life extension of therapeutic peptides. The project is part of the
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data. Manage preferences for further information and to change your choices. Accept all cookies Reject optional cookies Skip to main content Yale Quantum Institute Managing Director Employer Yale
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Carnegie Mellon University’s Robotics Institute is searching for a Postdoctoral Research Associate to join their team. This is an exciting opportunity for someone who thrives in an interesting and
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Institute. Using recent progress in machine learning and artificial intelligence, the successful candidate will have primary responsibility to develop, implement, and test multimodal machine learning