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the Computing & Engineering Department. The group is very dynamic, ambitious, well networked and delivers state-of-the-art research in a range of machine learning and data science topics, publishing research
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low-rank tensor network representations, which in principle enables the efficient simulation of physical systems in tensor network form. Besides the potential of enabling relatively frugal computations
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. The precise research topic(s) will be discussed with the successful candidate depending on their background, expertise and affinities. Analysis and publication of results Build a strong network in the field
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to help you prepare your relocation. In addition, Coming to Delft Service organises events to help you settle in the Netherlands, and expand your (social) network in Delft. A Dual Career Programme is
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addition to supporting user operations and SCS, the successful candidate will have the opportunity to pursue a research program under the supervision of the SINCRYS beamline scientist. The commissioning of a new
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researcher, you will play a central role in this ambitious programme and act as a technological integrator across multiple research tracks. You will work closely with three PhD candidates focusing on different
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qualifications: Must-haves: A completed PhD (or a PhD close to completion) in health economics, development economics, economics, econometrics, or a closely related discipline. Strong analytical and quantitative
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statistical / machine learning methods, pathway/network analysis or artificial intelligence approaches. Other requirements: The candidate should have a PhD or equivalent degree in bioinformatics, artificial
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to help you prepare your relocation. In addition, Coming to Delft Service organises events to help you settle in the Netherlands, and expand your (social) network in Delft. A Dual Career Programme is
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IOCB Prague (Institute of Organic Chemistry and Biochemistry of the Czech Academy of Sciences) | Czech | 2 months ago
across European life-science AI efforts. Requirements PhD in computational biology, bioinformatics, machine learning, or a related computational field Hands-on experience with foundation models / large