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Field
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training for transferable and soft skills, particularly research integrity, project management, writing, networking, career advice and coaching. Course organisation The PhD training programme combines
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– funded by the German Research Foundation (DFG) – offers a three-year, English-language doctoral programme with a highly complex, multidisciplinary field of research that provides our doctoral candidates
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strengthening international exchange. Moreover, BGTS researchers actively participate in international academic discussions and networks. Integrated internships The BGTS offers regular opportunities
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such as the following: astrophysics biophysics geophysics materials physics dynamics of complex systems particle physics solid state physics theoretical physics X-ray physics For further information, please
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Max Planck Institute of Molecular Plant Physiology • | Potsdam, Brandenburg | Germany | about 2 months ago
? How can we manage, analyse and integrate complex, large-scale genomic, epigenomic, transcriptomic, translatomic, proteomic and metabolomic datasets to answer biological questions and generate new
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28.07.2023, Academic staff Prof. Karen Alim’s group on Biological Physics and Morphogenesis at the TUM Campus Garching uses theoretical and experimental methods to investigate how flow networks self
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perceive, discriminate, and process the biological information encoded in CHC profiles remains poorly understood. PhD Position: The PhD candidate will investigate the chemoreception networks involved in CHC
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verbal communication skills. • Experience in teaching relevant subjects to university students. • Able to communicate complex and conceptual ideas to a range of groups. • Able to balance the pressures
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neural networks that handle the many challenges of integrating such complex medical data sources on large-scale studies and the translation to clinical practice. Qualifications PhD in (Bio-)Statistics
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Learning algorithms for EDA in terms of Computational Complexity, Performance Scores, etc. To learn more about our previous work, please check out our website ( www.cda.cit.tum.de/research/machine_learning