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Max Planck Institute for Astrophysics, Garching | Garching an der Alz, Bayern | Germany | 22 days ago
or distributed computing is an advantage Ability to work independently and collaboratively in an international research environment Working Environment and Mobility The position is embedded in a collaborative
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Max Planck Institute for Demographic Research (MPIDR) | Rostock, Mecklenburg Vorpommern | Germany | about 12 hours ago
candidates who have, or will soon obtain, a PhD in demography, sociology, epidemiology, medicine, health economics, biostatistics, public health, or a related field. The successful candidate is expected
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of analyses. Your profile A PhD e.g. in environmental science, ecology or related fields of biology or geography (or equivalent), or you have submitted your PhD thesis for assessment. Essential is experience
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22.12.2025, Academic staff We are an interdisciplinary team at the Chair of Safety, Performance and Reliability for Learning Systems, and we are looking for exceptional postdoctoral researchers
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standard software used for FRB or pulsar searches and analysis Practical experience in applying Machine Learning methods to data Experience with computer clusters and HPC Willingness to supervise Masters/PhD
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astronomy, physics, computer science or equivalent degree. PhD preferentially within the last 3 years. Solid background in star and planet formation or small bodies of the solar system Experience in
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results. Machine Learning skills to automise comparison process. Unbiased approach to different theoretical models. Experience in HPC system usage and parallel/distributed computing. Knowledge in GPU-based
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Senckenberg – Leibniz Institution for Biodiversity and Earth System Research (SGN), headquartered in Frankfurt am Main, is seeking to fill the following position at the Senckenberg Biodiversity and
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PhD/Postdoc position in trustworthy data-driven control and networked AI for rehabilitation robotics
of Information-Oriented Control we focus on research and teaching of control and optimization of cooperative, networked, and distributed dynamical systems. We develop novel methods and tools for the analysis and
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computer science with very good results - Interest on topics around the area of distributed systems and data management - Basic knowledge in distributed systems and graph algorithms is desired - Hand-on experience