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are invited to undertake a three-year PhD programme in partnership with industry to address key challenges in on-platform manufacturing engineering. The successful candidate will be based at the Rolls-Royce
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Administration, Entrepreneurship section, at Umeå School of Business, Economics and Statistics with Prof. Norbert Steigenberger as your main supervisor. With this PhD project, funded by Lundbergs Foundation, we
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into this important field. Additional input in computational aspects and analytical field-theory methods comes from our associated partners at Coventry University, UK, and the National Academy of Sciences of Ukraine in
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are looking for a highly creative and motivated PhD student with the following qualifications and skills: You have (or will obtain before the starting date) a (European) master's degree in computer science
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qualitative methods; some background in or willingness to learn computational social science methods as well as R and/or Python is highly desirable. Willingness to develop an ambitious empirical research
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ranges from core areas of computer science and electronics over medical applications to societal aspects of AI. SECAI’s main research focus areas are: Composite AI: How can machine learning and symbolic AI
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. The PhD position is within the Data-driven life science (DDLS) Research School. DDLS uses data, computational methods and artificial intelligence to study biological systems and processes at all levels
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Applications are invited to undertake a three-year PhD programme in partnership with industry to address key challenges in manufacturing engineering. The successful candidate will be based
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van Laar (University of Groningen), dr. Emar Maier (University of Groningen) and prof. dr. Jean Wagemans (University of Amsterdam). Other members of the project team are: prof. dr. Lilian Bermejo-Luque
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spectrum, in topics in virology and immunology, and currently specializes in computational biology focusing on developing methods and applications of deep learning for protein sequence and structure, as