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25.07.2025, Wissenschaftliches Personal Concerning a full position (100 %), we are hiring a Research assistant (f/m/d) at the Chair of Non-destructive Testing in the Project ScanPyramids OUR PROFILE
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: Reference number 3694: PhD student researching and developing alternative methods to animal testing (f/m/d) Pay grade: 13 TVöD Place of work: Berlin and Hannover Limited for three years Application deadline
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Description Reference number 3694: PhD student researching and developing alternative methods to animal testing (f/m/d) in the Experimental Toxicology and ZEBET department of the German Federal
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physics in action! Our international summer interns took to the mini golf course to test the limits of precision, patience — and putting angles Mechanics of Poking A Cyst New Paper from Shiheng Zhao and
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qualification (usually PhD). Tasks: The aim of the project is to design, model, fabricate and test a wireless micro-sensor which uses magnetic fields for sensing in biological soft tissues. For further
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Helmholtz-Zentrum Berlin für Materialien und Energie | Berlin, Berlin | Germany | about 18 hours ago
an understanding of the underlying magnetic processes through complex data analysis and computer simulations. You work in close collaboration with theoretical physicists to test models and develop new insights. Your
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developing 182Hf-AMS with the goal to detect traces of interstellar 182Hf atoms operating and optimizing an ion source for negative ions and testing with a series of ion beams support of SIMS measurements in
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for accelerator mass spectrometry developing 182Hf-AMS with the goal to detect traces of interstellar 182Hf atoms operating and optimizing an ion source for negative ions and testing with a series of ion beams
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positions)) contact information of two references for non-native speakers: proof of English language test not older than 12 months (e.g. TOEFL, IELTS, CAE) proven language skills can be: completed degree
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-training that facilitate few-shot adaptations. The research will show how the complementarity of event-triggered learning and meta-learning can drastically increase RL efficiency at test time. The co-design