91 computional-geometry-algorithm PhD positions at University of Groningen in Netherlands
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for realizing challenging asymmetric catalytic methods. This network brings together academic research groups with expertise in experimental catalyst development and theoretical groups skilled in computational
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(spoken and written). Preferred qualifications Prior experience with 3D cell culture, organoids, CRISPR-Cas9, or imaging-based phenotyping. Familiarity with transcriptomics or basic computational biology (R
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for Energy Business and Economics Research (CEnBER - https://www.rug.nl/cenber/ ) and in the research programme Economics, Econometrics & Finance of FEB’s Research Institute. The project will be supervised by
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-year PhD program, you will join a collaborative research team applying cutting-edge methods from Experimental/Behavioral Economics alongside modern macroeconomic modelling techniques (e.g. DSGE). You'll
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achieve both financial sustainability and social impact, and could provide guidance to MFI leaders, policymakers, and stakeholders. Organisation The PhD position is embedded in the research programme
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for considering components independently. Inspired by so-called contract theories from computer science, such modular control theory will be based on the introduction of assume-guarantee contracts for control
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to the development of a control theory that is inherently modular, i.e., that allows for considering components independently. Inspired by so-called contract theories from computer science, such modular control theory
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achieved consensus. The PRELIFE consortium brings together leading researchers from a wide spectrum of disciplines—including astronomy, biology, chemistry, computer science, earth and planetary sciences
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communication skills are encouraged to apply. A MSc degree (or equivalent) in Mechanical Engineering, Computational Physics, Materials Science or a related discipline is required, with experience in atomistic
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Engineering, Computational Physics, Materials Science or a related discipline is required, with experience in atomistic modelling of materials and machine learning. Experience in atomistic modelling (molecular