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. Expertise in some of the following areas is expected: Expertise in quantum information processing, quantum optics, or related fields. Strong experimental skills and solid theoretical understanding of quantum
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agreed upon with the relevant union. The period of employment is 2 year. Starting date as soon as possible in the new year. You can read more about career paths at DTU here . Further information Further
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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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about career paths at DTU here . Further information Further information may be obtained from Professor Yi Sun (suyi@dtu.dk ). You can read more about DTU Health Tech at www.healthtech.dtu.dk . If you are
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. Further information Further information may be obtained from Professor Wei Yan, tel.: +45 2245 0662, email: weya@kemi.dtu.dk . You can read more about Department of Chemistry on www.kemi.dtu.dk If you are
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the Danish economy using administrative data and identify the role of social power in the redistribution of income shares among salient social groups (e.g. workers, managers, owners and founders) drawing
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interest in information processing in humans and computers, and a particular focus on the signals they exchange, and the opportunities these signals offer for modelling and engineering of cognitive systems
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adjustment and plate tectonics. The analysis will encompass both network wide and local analysis using data from Greenland GNSS Network (GNET). You will target specific regions where there can be an unresolved
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computer architecture. Responsibilities and qualifications You are expected to conduct independent research in collaboration with and under the guidance of experienced colleagues. Additionally, you will be
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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