26 phd-in-mathematical-modelling-of-biochemical-reactions Postdoctoral positions at Aarhus University in Denmark
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qualifications at the PhD level in animal science Research experience in dairy cow nutrition and feed evaluation Research experience with the use of stabile isotopes and modelling rumen flows Experience in
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computational models to map co-expression networks and predict systemic disease transitions. Characterise intestinal microbiome changes and their correlation with inflammatory diseases. Computational modelling
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Do you have experience with modelling structures subjected to dynamic loading? Are you interested in data-driven methods for modelling applied loading? Are you eager to share your knowledge within
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nitrogenase catalyzed ammonia synthesis in the triple-phase reactor. Your profile Completed PhD in the field of Biotechnology, Biochemistry, Biochemical Engineering, Molecular Biology, or a relevant, Strong
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the Director of Center for Music in the Brain. Your competences You have academic qualifications at PhD level, for example within the following areas of neuroscience, engineering, mathematics, medicine
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background in feed processing technologies, biochemical, and chemical evaluation methods. Proven experience in experimental design, data analysis, scientific communication and writing. Demonstrated ability
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five bioclimatic zones. Your task will be to combine multi-source data — including field observations, environmental measurements, and satellite imagery — with mechanistic models to assess carbon
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of responsible and human-centered AI in software engineering (AI4SE). The AI4SE1DK project addresses urgent industry needs by investigating how Large Language Models can be effectively, ethically, and sustainably
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engaging research environment. The postdocs will work on cultural alignment and preference optimization of large language models (LLMs) for mid to low-resourced languages. The overarching goal is to develop
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to integrate various structural biology data (NMR, SAXS, FRET, EPR) as well as computational models and simulations to create and interpret conformational ensembles of disordered protein regions, with the goal