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in Austria. We are seeking a PhD candidate on predicting adherence to digital health-promoting interventions with Artificial Intelligence (AI) and machine learning (ML) techniques. You will develop AI
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(or equivalent) in Computer Science, Artificial Intelligence, Engineering or a closely related field; Solid background in machine learning and/or evolutionary optimisation; strong programming skills (Python/C
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Computer Science, Artificial Intelligence, Engineering or a closely related field; Solid background in machine learning and/or evolutionary optimisation; strong programming skills (Python/C++); Proven interest in
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an enthusiastic young scientist eager to work at the intersection of neuroscience, artificial intelligence, and medicine? Do you hold a Master’s degree that has equipped you with strong skills in
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range of science and engineering disciplines, from classical disciplines such as mathematics, astronomy and mechanical engineering, to interdisciplinary fields such as artificial intelligence,nanoscience
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Description We are looking for a PhD-candidate interested in topics that lie on the border of optimization by the use of heuristic algorithms and (Explainable) Artificial Intelligence ((X)AI). Specifically, in
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that has been generated in a prior laboratory-setting project. Specifically, we will integrate recent advances in artificial intelligence-based automated interpretation of medical images, and new knowledge
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on research, with optional contributions to education and supervision of students. Job requirements You have a master's degree in computer science, artificial intelligence, or mathematics. You can demonstrate
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, Education, Artificial Intelligence or a related field; The skills and knowledge for in-depth automated text analysis and the development and use of text quality metrics; The skills and knowledge for carrying
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lengthy processing times associated with sequencing. This PhD project aims to develop innovative artificial intelligence (AI) methodologies by integrating histopathology images and RNA sequencing data