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investigate and develop innovative memory solutions in advanced CMOS technologies such as FDSOI. The development of integrated circuits also plays an important role in making these networked devices and their
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architectures and principles from Bayesian neural networks and biological sequence models, including large DNA and protein language models. The project also aims to develop a prototype federated learning
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post-doc levels in a single and unique structure. Within the Berlin School of Economics, Humboldt-Universität zu Berlin , Freie Universität Berlin , Technische Universität Berlin , University of Potsdam
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and work independently Excellent cooperation and communication skills and ability to work as part of a team Excellent skills in spoken and written English Our Offer: We work on the very latest issues
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; Phone: +49 (0) 345 5582 1720 Applications must include a cover letter describing research accomplishments and interests, a CV plus publication list, and contact details of 2 referees. Please send your
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to be developed. One promising research direction is the use of physics-informed deep learning, such as physics-informed neural networks or deep neural operator networks. Tasks: Work in a team on national
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on electrochemical systems Experience in one (or more) of the following areas is desirable: electrochemistry, electrocatalysis, additive manufacturing (spray coating, doctor blade, slot-die coating), electrochemical
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contact details of 2 referees. Please send your complete application documents including the reference number 14/2025 exclusively by email to bewerbungen at ipb-halle.de . Review of applications begins
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vegetative fossil specimens of gymnosperms from the collections of the Senckenberg networks as well as other collections around the world Score traits from vegetative fossils of gymnosperms from the Jurassic
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Degree Doctor of Philosophy (PhD) in Medical Research – Cardiovascular Science Course location München Teaching language English Languages Courses are held in English only. PhD theses are written