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wide range of theoretical perspectives, methodological approaches, and links to educational practice. The interdisciplinary course program focuses on the processes and outcomes of teaching and learning
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events are foreseen, applicants must be ready to travel Applicants must be eligible to enroll on a PhD program at TU Dresden (see https://tu-dresden.de/ing/maschinenwesen/postgraduales/promotion
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research with the combined tools of immunology, microbiology, virology, cell biology and molecular biology. For more information, please see https://www.mhh.de/hbrs/zib MD/PhD Molecular Medicine
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simulation environments, numerical methods, or machine learning approaches is an advantage Fluent command of written and spoken English is necessary; German is an advantage but not required High degree
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to teach in German and English We offer: opportunity to work in an international environment participation in scientific exchange programs and short research stays abroad membership in the Graduate Academy
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machine learning approaches. These are similar to earlier work on charge and excitation energy transfer (see https://constructor.university/comp_phys). The project for the PhD fellowship is slightly more
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, storage, accessibility/sharing, archiving, publication, and preparing data for machine learning applications. The Research Training Group RTG 3120 offers, subject to the availability of resources, a
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candidate will be embedded in the DFG Research Program RTG3120 on Biomolecular Condensates ( https://dresdencondensates.org ). Each PhD project is part of an interdisciplinary framework that includes shared
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knowledge of machine learning (e.g., in the areas of object detection and identification, generative AI, etc.) Good written and spoken English skills (min. level B2) Good written and spoken German skills (min
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their achievements and productivity to the success of the entire institution. At the Faculty of Electrical and Computer Engineering, Institute of Solid State Electronics, Chair of Coating Technologies in Electronics