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interdisciplinary doctoral program starting July 2026. 🔬 What we offer Join a highly collaborative, DFG-funded research environment that brings together experts from physics, chemistry, biology, and materials
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geophysics, physics, geoscience, computational geoscience, or related natural sciences with an overall grade of at least good Experience in programming (e.g., MATLAB, Python, C/C++) Advanced knowledge
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, physics or a similar area - very good programming skills in Python - good prior experience with neural networks using common Python-ML libraries such as PyTorch - background knowledge in computational
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concept, research program) should be submitted online via https://berufungen.uni-stuttgart.de by May 06, 2026, addressed to the vice dean Prof. Dr. M. Daghofer. Please send postal applications
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Applicable Offer Starting Date 1 Sep 2026 Is the job funded through the EU Research Framework Programme? Horizon Europe - ERC Is the Job related to staff position within a Research Infrastructure? No Offer
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/11250664 https://www.jmlr.org/papers/v26/25-1161.html Job Specifications For PhD applicants: Excellent Master’s degree (or equivalent) in engineering, computer science, or related disciplines (typically
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HBIGS Heidelberg Biosciences International Graduate School | Heidelberg, Baden W rttemberg | Germany | 6 days ago
links to the group of Motomu Tanaka (Physical Chemistry), Thomas Holstein (COS) and others. Selection process Please submit your application through the HBIGS application system: https://www.hbigs.uni
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process; it remains unaffected. Objective: The aim of this master's thesis is the development and systematic evaluation of training strategies that dynamically adjust the training process at runtime based
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Physics (KCETA) at KIT (Germany). The MSCA COFUND program KSETA Europe is now accepting applications for doctoral researcher positions starting in October 2026 or later. Our PhD program leads to a doctoral
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to make them usable for transparent energy system analyses. You will process and semantically enrich the collected data before it is integrated into a knowledge-graph-based metadata platform. In