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these with quantitative and qualitative research methods to promote a regenerative food system in the Netherlands? If you have a PhD degree and a skill set that puts you in a good position to carry out
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. You’ll be part of a dynamic, collaborative environment that values innovation, rigor, and translational impact. Information and application Apply by 23:59 on August the 21th, 2025. Interviews will
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to build predictive models Collaborate closely with experimentalists and modelling experts Project Environment This position is part of a collaborative research project involving: Two PhD students at TU
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research). Our research focuses on questions within the domains of food, living environment, and society. With approximately 30 locations, 7,700 staff members, 2,500 PhD candidates, and over 13,000 students
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, Computer Science and Artificial Intelligence. The position is embedded in the Multi-Agent Systems group of the department of Artificial Intelligence of the Bernoulli Institute. Qualifications PhD in Computer Science
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exoskeletons and bionic limbs. You’ll be part of a dynamic, collaborative environment that values innovation, rigor, and translational impact. Information and application Apply by 23:59 on August the 24th, 2025
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. Qualifications PhD in Computer Science, Economics, Mathematics, or a closely related dis-cipline. Strong background in computational social choice, algorithmic game theory, or AI safety. Excellent research track
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. You’ll be part of a dynamic, collaborative environment that values innovation, rigor, and translational impact. Information and application Apply by 23:59 on August the 24th, 2025. Interviews will
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the inspiring research group of Economic and Social History external link , one of the world-leading groups in the field. Your qualities You bring the following qualifications: a PhD in social, economic and/or
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used in home environments allow for multi-night recordings which is essential to reduce the impact of night-to-night variability of OSA severity on classification. In addition, non-contact detection