36 algorithm-development-"Multiple"-"Simons-Foundation"-"Prof" "UNIS" positions at Utrecht University
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Professor Appy Sluijs, and close collaboration in this project will be with Dr. Peter Bijl. Multiple others will be involved for specific aspects of the project, including several scientists involved in
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of the Debye Institute for Nanomaterials Science, with access to research schools, colloquia, career events, and social activities. Your job This PhD project aims to develop a nanostructured bijel
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University, you will develop innovative methods to make geographic data smarter and more question-aware, contributing directly to the future of spatial reasoning and sustainability. Your job Answering
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knowledge flows between researchers, companies, and regulators, and develop practical tools and strategies to accelerate the shift toward animal-free methods. Your work will combine advanced quantitative and
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and with groups in the Life Sciences, particularly in the Departments of Chemistry and Biology. You will develop an independent research line based on your strong and proven expertise in the field
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such cases, maps must be created or transformed from data rather than simply retrieved. The GeoTrAnsQData project addresses this by developing a GeoQA method that converts questions into executable geo
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work closely with the Utrecht University team and OpenGeoHub together with other project partners, to develop surrogate and hybrid modelling frameworks combining process-based models with data science
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learning with emerging technologies involving extended reality. We focus on how, when, why, and who benefits from using these technologies. The goal of our work is to develop evidence-based knowledge
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, pathologists, led by PI/Assistant Professor Dr. Lonneke IJsseldijk. This position offers a dynamic and professional work environment with opportunities for professional development, including training through
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work closely with the Utrecht University team and OpenGeoHub together with other project partners, to develop surrogate and hybrid modelling frameworks combining process-based models with data science