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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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learning and knowledge-based methods, you will tackle high-dimensional biological data to uncover new insights into the connections between nutrition and health. In addition to your research activities, you
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the University Teaching Qualification (UTQ). The candidate will also contribute to research on commissioned projects, take the initiative to write tenders and research proposals to acquire new research projects
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(adaptive) imaging strategies and reconstruction. The research combines ultrasound physics, signal processing, machine learning, computational imaging, and clinical translation. Beyond your individual
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); teach and co-develop inspiring and high-quality courses in Bachelor and Master Programmes of the school of Innovation Sciences; initiate and contribute to externally funded research projects; assist in
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positions that are strictly temporary. You are expected to teach in the academic year 2026-27. The selected candidate(s), will be expected to start teaching as early as September 2026 or soon thereafter. What
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(eventually) committees Be committed to obtaining a university teaching qualification, or possessing one already. Where to apply Website https://www.academictransfer.com/en/jobs/362533/assistant-professor-in
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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
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., in Python. A keen interest in interdisciplinary research. An excellent command of English, as you’ll be working in an internationally diverse community and with international partners. Ability to learn
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to apply Website https://www.academictransfer.com/en/jobs/363316/11-phd-positions-in-the-excelle… Requirements Specific Requirements An outstanding, motivated, enthusiastic, curiosity-driven researcher. Deep