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transcriptomics data is an advantage. We offer: A 3-year postdoc position in a supportive, stimulating, and interdisciplinary research environment Training in a wide range of scientific and transferable skills
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candidate is expected to contribute to the overall objectives of the project by being involved in the project management, data collection, and data analysis. The candidate is also expected to contribute
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writing scientific papers. The developed models will be tested on data from energy investment models, as well as transport infrastructure problems. We will be an academic team of three PhD students and four
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an ERC Advanced Grant and a Laureate Grant from the Novo Nordisk Foundation. We are now looking for 1-2 postdoc researchers with a PhD and/or MD (i.e. level of education corresponding to the Danish PhD
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for professional development and training towards an independent research career. Responsibilities and qualifications We are looking for creative and ambitious researchers with PhDs in chemistry, materials science
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information on the Department is linked at https://www.science.ku.dk/english/about-the-faculty/organisation/ . Inquiries about the position can be made to professor Knud J. Jensen. The position is open from
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interdisciplinary DIGIFABA project, aimed at enhancing the sustainability and climate resilience of grain legume production through digital phenotyping, advanced data science methodologies, and mechanistic modelling
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predictive framework linking genomic data to extinction risk, working at the interface of evolutionary genomics, simulation modelling, and machine learning. By integrating forward-in-time simulations, real
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outlook. We expect you to have good communication and personal interaction skills and to be fluent in English. As a formal qualification, you must hold a PhD degree (or equivalent). Further information
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create multi-fidelity predictive models that integrate data from quantum simulations and experiments, using techniques such as equivariant graph neural networks with tensor embeddings. We aim to train