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Other relevant professional activities Curious mind-set with a strong interest in enzyme structure and function An ability to learn new skills An ability to interact professionally with other scientists
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Project, combined with advanced statistical methods, machine learning techniques and data from wearable sensors. Collaboration with clinicians, data scientists, engineers, researchers and patient
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and validated within the PhLAM team. Consequently, only limited effort will be required to acquire the experimental skills needed for this part of the project, allowing the PhD candidate to focus
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learning techniques for tool health monitoring and prognosis. Dissemination of research results through scientific publications, conference presentations, and completion of a PhD thesis. Required skills
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, with the earliest start date 1 November, 2026. Further details and application instructions are available at: https://math.au.dk/en/about/vacancies/phd The webpage includes brief subject descriptions and
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Strong Python skills and experience with data manipulation Basic machine learning knowledge (equivalent to at least an introductory course) Additional skills (nice-to-haves) Experience with website
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researcher is expected to become member of The Vienna Doctoral School of Philosophy. For more information, see https://vd-philosophy.univie.ac.at/ The successful candidate will: finalize their dissertation
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an international peer-review system Publications within the project’s research area Training in higher education teaching and learning Experience researching innovation and patenting in historical perspective
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to the IE faculty's Doctoral Programme (https://www.ntnu.edu/ie/research/phd/), see Section 6-1 of the PhD regulations for more information. You must have a relevant Master's degree in Computer Science and
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are leading internationally in their respective disciplines and provide an exciting and collaborative environment, with room to learn and develop professionally at the frontier of academic research. You will