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Are you interested in neuromorphic spintronic and can you contribute to the development of the project? Then the Department of Electrical and Computer Engineering invites you to apply for a one year
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-friendly working environment Sustainable travel to work: subsidized Germany job ticket Our Corporate Health Management Program offers a holistic approach to your well-being Develop your full potential
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multidisciplinary environment of biologists, clinicians, computational scientists, and other colleagues within our research groups and with consortium partners of the FOR 5806 Your Profile We are looking for a self
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program at the interface of drug delivery, biomaterials, and cancer biology. The successful candidate will play a key role in developing next-generation therapeutic platforms, including lipid nanoparticles
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academic backgrounds to contribute to our projects in areas such as: Network Security, Information Assurance, Model-driven Security, Cloud Computing, Cryptography, Satellite Systems, Vehicular Networks, and
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academic backgrounds to contribute to our projects in areas such as: Network Security, Information Assurance, Model-driven Security, Cloud Computing, Cryptography, Satellite Systems, Vehicular Networks, and
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natural and AI-designed protein domains, along with an engineered fusogenic protein. The technology has been recognized with the m4 Award, the GO-Bio next program, and is currently under revision in a top
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to understand cancer development and to develop new therapeutic strategies. The Fred Hutch/University of Washington Head and Neck Research Program- Fred Hutch and the University of Washington have a world-class
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Postdoc Position in Models of Quantum Programming Languages (Sapere Aude: DFF-Research Leader Pro...
The Department of Mathematics and Computer Science at the University of Southern Denmark, Odense, invites applications for a postdoctoral research fellowship in models of quantum programming
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description You will be contributing to developing and implementing novel algorithms at the intersection of computational physics and machine learning for the data-driven discovery of physical models. You will