27 physical-engineer "Data driven Materials Modeling" Postdoctoral positions at Utrecht University
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17 Jul 2026 Job Information Organisation/Company Utrecht University Research Field Biological sciences » Biological engineering Biological sciences » Biology Researcher Profile Recognised Researcher
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, Information & Computing Sciences, Physics, Chemistry and Mathematics. Together, we work on excellent research and inspiring education. We do so, driven by curiosity and supported by outstanding infrastructure
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data to learn contextual representations of microbes and communities and translate them into predictive models for successful crop microbiome engineering. Your job Plant-associated microbiomes can
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microbiome and genome data to learn contextual representations of microbes and communities and translate them into predictive models for successful crop microbiome engineering. Your job Plant-associated
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the pragmatism that is needed to move a project forward. By the time the position starts, you have obtained a PhD degree in Data Sciences, Computer Sciences, Physics, Earth Sciences, Civil Engineering, or a
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challenging organisation. The Faculty of Geosciences is organised in four Departments: Earth Sciences, Human Geography & Spatial Planning, Physical Geography, and Sustainable Development. More information For
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-modelling skills with an interest in societally relevant freshwater challenges. You bring: A PhD in hydrogeology, physical geography, earth sciences, civil or environmental engineering, or a closely related
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example regarding your workplace Martinus J. Langeveldgebouw external link , the application process or your work, please contact us via our HR contact page external link . More information For more
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, to eventually capture them in physical-chemical models that predict the impact of acidification on marine P cycling. The PHOSFLUX project is a collaboration between the NIOZ (dr. Peter Kraal) and Utrecht
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create healthy physical activity-related habits. As a postdoctoral researcher, you will lead the development of an innovative AI-enabled recommender system for urban (re)design. The system will combine