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Mathematical and computational methods to design and analyse biological systems Engineering biology to address current challenges in sustainability Creating new technology for the interrogation of cells
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us We are TUM’s unique Pathology AI lab developing new machine learning (ML) methods for automatically analyzing digital pathology data and related medical data. Such methods include the automatic
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experience in the methodical and analytical development of energy system models with programming skills, preferably in Python Experience in the successful acquisition of third-party funded projects and in
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methods courses and courses on advanced neuroscience and transferable skills, make excursions to research institutions and companies and participate in summer schools, seminars and international meetings
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Max Planck Institute for Human Cognitive and Brain Sciences • | Leipzig, Sachsen | Germany | about 2 hours ago
neuroscience and cognition to the development of novel methods in neuroimaging, computational neuroscience, and artificial intelligence. To cover this spectrum and provide top scientific quality, the IMPRS CoNI
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-disciplinary and cross-cultural cooperation. The research revolves around four topic areas: Business models, decision processes and economic analyses Holistic interdisciplinary methods for modelling, analysis
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organisation To achieve valuable scientific results, talented PhD students need to acquire knowledge and are also required to exchange knowledge and experience with other PhD students in method-oriented working
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symposium Advanced methods and specialised training Transferable skills and career development Other curricular activities including an IMPRS-ML retreat In addition to the curricular activities organised by
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country and life situation. To calculate this amount individually please use our fellowship calculator. Travel expenses are reimbursed in addition. Information on sponsorship during the research stay
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, (food) marketing, or related social sciences disciplines, strong analytical skills, experience with relevant statistical methods, proven interest in topics related to sustainable food systems, and strong