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Description In the Department of Mathemathics and Natural Sciences in the Group Technical Physics I at the Technische Universität Ilmenau (Germany) is a vacancy for a PhD Position (f/m/d) in Growth
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Description 3 x Academic Researcher (m/f/d) (TV-L E 13, 100%, Service Location: Clausthal-Zellerfeld) The research group Dependable and Autonomous Cyber-physical Systems (DACS) at the Institute
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methods to study RNA phage-induced complexome remodeling and decipher the molecular mechanisms and consequences of this process. Requirements: Master’s degree/Diploma or equivalent in biology, biochemistry
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15, 2025. For more information on the PhD program and the application process, please visit our website at www.geschkult.fu-berlin.de/hcs . If you have any questions about the call for applications
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; degrees in Chemistry, Physics, Biochemistry, Chemical Engineering, or a related discipline will be accepted. At the time of the nomination (estimated January 2026), your last final exam should have taken
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years. In total there will be about 25 doctoral researchers who will conduct soft matter research combining fields as diverse as physical chemistry, spectroscopy, synthetic organic and polymeric synthesis
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of globalization. Application Process: Candidates are selected in a two-step process by GSGAS and DAAD. Candidates are nominated during the selection process by the GSGAS to the DAAD. The final decision is made by
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demands. To break this bottleneck and cut simulation time by orders of magnitude, you will design and implement surrogate models that learn the behavior of full‑physics codes using modern machine‑learning
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the field Requirements: MSc in Physics, Mathematical/Theoretical Biology, or Chemical Engineering Very good written and spoken English skills Curiosity about the mechanisms underlying life and disease Self
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of neural hydrology, where hydrological models are directly learned from data via machine learning (e.g., LSTM neural networks, [1]). Initially, these models ignored all physical background knowledge and did