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)biodiversity and conservation genetics applied to wildlife and model organisms. The selected candidate will contribute to this important transition by integrating our vibrant team and by engaging in
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range of fields including applied cyber-physical systems, artificial intelligence, embedded computing, mechanical structure integrity and life assessment, heating and cooling, renewable energy systems
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, entrepreneurship, and work-life balance. Be part of a university that values innovation, societal impact, and diversity. In this position you will develop and lead a research program focused on applying quantitative
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information from medical images, improvement of image quality to support dose calculation and adaptive treatment delivery, and statistical modeling of patient data as well as development of efficient methods
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programme management as well as contributions to the development of teaching activities and teaching material. Emphasis is placed on the extent, to which the applicant, has developed the academic discipline
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, artificial intelligence (AI), machine learning, and computation have emerged as powerful digital technologies for creatively generating new design ideas and rapidly advancing formgiving methods within
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programs, and 4) dissemination with high visibility and broad societal impact. The applicant is expected to contribute to the teaching program at the Department in the Bachelor and Master’s programs in
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engineering, operations research, computer science, economics, or a related field. You must have demonstrated track record with publications in recognised and leading journals based on experience in developing
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candidates with expertise in one or more of the following specialized areas: Machine Learning / Deep Learning Uncertainty Quantification Wind Farm Flow Modelling Wind Farm Control Wind Farm Design Wind Farm