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disease models. The emphasis will be on the communicative potential of these vesicles in the gut-brain-metabolic axis. The LHMI group operates a state-of-the-art molecular biology laboratory and maintains
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results with AI models and system simulations to create a digital twin of the PtX process for predictive optimization and scenario analysis. Funding This PhD position is generously funded through the Villum
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will conduct sampling, and apply experimental methods such as metagenomics and metatranscriptomics, linked to soil and emission data to help create predictive models. Within a broader framework, your
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-objective optimization, and online decision-making approaches are relevant areas of expertise for this position. Previous experience with developing models, tools, or processes is desired. The candidate has
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Job Description RISC-V open source and open standards as the nucleus for new platform models help to improve overall flexibility and productivity for a wide market access. Given the challenge
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of computational chemistry. Applicants can have a background from cheminformatics including RDKit, machine learning applied to chemistry, and molecular modeling Our group and research- and what do we offer? Our
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, electrolysis, power-to-x, batteries, and carbon capture. The research is based on strong competences on electrochemistry, atomic scale and multi-physics modelling, autonomous materials discovery, materials
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modelling approaches will also be used to complement the experimental work. The bioprocess engineering team at DTU Chemical Engineering consists of around 10 scientists and engineers. Expertise is available
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range of advanced functional genomics methods, particularly single-cell technologies, in pre-clinical model systems such as cell lines and patient-derived tumor organoids as well as patient samples
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model checking. You should be well versed in basic statistics and practical programming skills is a must. Knowledge about the inner workings of GenAI would be nice but not necessary. You must have a two