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, you will carry out research that is theoretically and societally relevant as well as methodologically and ethically sound by means of collecting and analysing in-depth qualitative data. Within four
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on real-life issues that have a huge impact on society, economics and ecology: from robotics to big data, and from job market participation to change management. Collaboration and cooperation, transparency
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understanding of tissue growth and inform in vitro experiments? Then you might be our next PhD candidate! Information Functional and durable regeneration of articular cartilage is still an unsolved challenge
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employment conditions through our Terms of Employment Options Model. In this way, we encourage you to keep investing in your personal and professional development. For more information, please visit Working
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plus if you additionally have experience with robotics, physics engines or simulators, causal inference, or biomedical / scientific data — and any track record of research output (thesis, preprints, open
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encourage you to keep investing in your personal and professional development. For more information, please visit Working at Utrecht University . About us A better future for everyone. This ambition motivates
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PhD Candidate: Modulating plant-based nutrition to enhance the sensory aspects and nutritional value
within the field; Complete a PhD thesis within 4 years; Analyze data and present research outcomes at group meetings, national and international conferences, and consortium meetings; collaborate with a
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for a sustainable, healthy and just future. From forest fires to big data, from obesity to malnutrition, from helium to the universe and from genetics to medicine: our education and research cover
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, scientists and students work on fundamental and complex societal issues for a sustainable, healthy and just future. From forest fires to big data, from obesity to malnutrition, from helium to the universe and
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self-assembly of ligand building blocks will be generated and explored. Detailed kinetic data gathered during these studies will also contribute to machine learning (ML) approaches in collaboration with