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existing methodologies. Carry out literature review, hypothesis development, and experimental design. Adapt, develop and learn new tools, software, and methodologies independently. Present and publish
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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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courses or doctoral candidates Selection Selection is made by the National Science and Technology Council - NSTC Further information National Science and Technology Council - NSTC https://www.nstc.gov.tw
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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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Portal https://securemail.tu-dresden.de by sending it as a single pdf file to uwe.hampel at tu-dresden.de or to: TU Dresden, Chair of Imaging Techniques in Energy and Process Engineering, Prof. Dr
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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