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Field
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background in Computer Science, Informatics Engineering, Mathematical Modeling, Computational Urban Science, Transport Modeling or equivalent, or a similar degree with an academic level equivalent to a two
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Organisation Job description For the National Growth Fund (NGF) project “Groeien met Groen Staal” (GGS), a PhD position for the period of 4 years is available in the context of modelling green steel
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combines microbial genomics, transcriptomics, and in vitro infection models to explore the adaptive trade-offs between drug resistance and virulence phenotypes. The position is funded for 3 years and
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development. Our individual choices model gives you some freedom to assemble your own set of terms and conditions. For international spouses we have set up a dual career programme. Candidates from outside
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of the following areas and an interest to develop within others: Protein chemistry Enzyme kinetics and kinetic modelling Experimental physical chemistry Electrochemistry Assay development and
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innovative machine learning architectures for the mining, prediction, and design of enzymes. Combine state-of-the-art ML (e.g., deep learning, generative models) with computational biochemistry tools
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of this PhD is to use optical flow visualisation and measurement techniques to study droplet impact under icing conditions to improve icing codes that aid in design and development of ice detection and
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designs, building effective and conceptual models to inform our theoretical understanding, and developing code and theory frameworks to address new topological phenomena. Depending on the project’s results
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you like to contribute to an increased understanding of carbon cycle feedbacks in the climate system? Do you thrive in the dynamic blend of seagoing fieldwork, laboratory experiments and modelling? As a
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), we aim to close this gap, by developing AI models and tools for tabular data, to help organizations, of any size, domain, and level of data literacy, get insights from structured data, efficiently