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Field
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willingness to learn: High-performance computing (distributed systems, profiling, performance optimization), Training large AI models (PyTorch/JAX/TensorFlow, parallelization, mixed precision), Data analysis
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2 Sep 2025 Job Information Organisation/Company Friedrich Schiller University Jena Department Psychiatry and Psychotherapy Research Field Neurosciences Computer science Mathematics Engineering
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processing methods, mechanistic computer models and software tools and to use them in highly relevant clinical, biotechnological and pharmaceutical applications at the forefront of research. All projects
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Germany Application Deadline 7 Dec 2025 - 22:59 (UTC) Type of Contract To be defined Job Status Other Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job
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). The institute also maintains locations in Dedelow and Paulinenaue. The position will be based in the Research Platform “Data Analysis and Simulation“ within the Working Group “Ecosystem Modelling“ under
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genomic approaches Application of the modeling approaches in relevant downstream tasks Co-development of high-performance computing AI training codes for the first European Exascale Supercomputer JUPITER
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Max Planck Institute for Astrophysics, Garching | Garching an der Alz, Bayern | Germany | 3 days ago
Mellon University, the Max Planck Institute for Astrophysics (MPA), and further institutions, have embarked on an ambitious program to improve our constraints on the initial conditions of the Universe
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Deadline 7 Dec 2025 - 23:00 (UTC) Type of Contract To be defined Job Status Full-time Hours Per Week To be defined Is the job funded through the EU Research Framework Programme? Not funded by a EU programme
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Max Planck Institute for Dynamics of Complex Technical Systems, Magdeburg | Magdeburg, Sachsen Anhalt | Germany | 25 days ago
computational methods to analyze these models and identify suitable intervention strategies maximizing the synthesis of specific products. Using experimental data to improve the models and to support an iterative
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technology that will make it possible to publish, combine, and preserve statistical models for physics experiments and beyond, and to make them usable across programming languages (C++, Python, and Julia