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invasive sensing tools to monitor metabolites, oxygen, carbon dioxide, pH, and other parameters. Ideally, the methods can function in parallel and on a large scale. The research is vital to understand key
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of cloud microphysical processes, with the goal to better understand clouds and their interactions with other Earth system components. Using this framework, we strive for a high degree of process-level
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of the English language Ideally, you have experience with version control (e.g., Git), concurrency and parallelism, inter-process communication, and containerization (e.g., Docker). What you can expect Insight
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are expected. Knowledge in parallel programming is desirable. Prior knowledge in differential-algebraic equations, Gaussian processes or kernel based methods is a plus; programming experience in Python or C/C
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optical communication networks and systems, as well as machine learning, computer vision and compressing digital videos. Since 2020, Fraunhofer Heinrich Hertz Institute has worked with United Nations
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, we seek a highly motivated researcher with a proven track record in parallel programming models for CPS, high-level compilers, system and computer architecture and automatic code optimization
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the REACT Doctoral Network. In this context, we seek a highly motivated researcher with a proven track record in parallel programming models for CPS, high-level compilers, system and computer architecture and
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to scientists and investigate possible applications of ML in fields like Chemistry, Numerics, Computational Biology, Astrophysics, Heliophysics etc.. You will be involved in all phases of this process. You will
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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
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invasive sensing tools to monitor metabolites, oxygen, carbon dioxide, pH, and other parameters. Ideally, the methods can function in parallel and on a large scale. The research is vital to understand key