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and qualifications. Possible topics are: The theory of ultrafast pump-probe experiments (e.g., time-resolved X-ray scattering and spectroscopy), simulations and data processing of actual ultrafast
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the identification and development of data-driven models that can subsequently be used for system optimization. The project encompasses both algorithm design and experimental implementation. Close collaboration and
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student to join our dynamic and interdisciplinary research team in the Section of Construction Materials and Durability at DTU Sustain. Through advanced experimental work and modelling, you will help
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models that integrate data from quantum simulations and experiments, using techniques such as equivariant graph neural networks with tensor embeddings. We aim to train these methods in a closed-loop
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master's degree. The successful candidate will have a degree in chemistry, chemical engineering, biochemistry, or biophysics. Experience with experimental organic chemistry, NMR, kinetic modelling and/or
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copy of the Diplomas + the official English transcript of the academic degrees and academic records. (In the case an applicant doesn’t hold the official transcript at the moment of application, he/she
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and sustainable biomanufacturing. However, little is known about non-model gas fermenting microorganisms. The focus of the advertised positions will be on mapping the metabolism of gas fermenting
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Analytics. The core focus of the PhD project will be to develop and test planning and optimization models to analyze new and innovative Hospital-at-Home systems to improve access to healthcare for elderly and
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the applicant, rather than by a language model. We offer DTU is a leading technical university globally recognized for the excellence of its research, education, innovation and scientific advice. We offer a
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leverage the power of field-programmable gate arrays (FPGA) to deploy machine learning models on the edge with low latency and high energy efficiency. This added intelligence will enable the rapid evaluation