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to the development of innovative, physiology/ machine learning-driven clinical solutions and decision support tools for critically ill patients, focusing on cardiovascular and respiratory monitoring, mechanical
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Vacancies Academic staff Support staff UT Student Jobs UT as employer UT as employer Employment conditions Career and development Pre and onboarding Tenure Track PhD EngD Working as a UT student
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Vacancies Academic staff Support staff UT Student Jobs UT as employer UT as employer Employment conditions Career and development Pre and onboarding Tenure Track PhD EngD Working as a UT student
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Vacancies Academic staff Support staff UT Student Jobs UT as employer UT as employer Employment conditions Career and development Pre and onboarding Tenure Track PhD EngD Working as a UT student
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, limiting user understanding, contestability, and trust. In this PhD position, you will contribute to the development of a transparent AI system to support behavioural change in nutrition. You will integrate
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-scale development and implementation of green hydrogen in the Netherlands and across Europe. The programme addresses the system-wide conditions required to enable a successful hydrogen transition
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aims to contribute to health maintenance and personalized medicine by unravelling lifestyle and disease-induced derangements in metabolism, and by developing targeted nutritional, exercise and drug
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position focused on the development of 3D LPT techniques for industrial applications. Job description In this Postdoc position, you will focus on the development of large-scale three-dimensional Lagrangian
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for their governing mechanisms? How can we make these model computationally efficient and capable of scaling to large dataset sizes? Scientific challenges for this exciting PhD project include: develop principled
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ESA projects, managing R&D activities, advancing technology development, contributing to the Agency’s technology programmes and fostering innovation. Additionally, the Discipline Engineer supports