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-based principles. The successful candidate will train, benchmark, and develop deep learning architectures. They will work in high-performance computing environments and apply expertise in statistical
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/MS workflows, spectral library searches and data curation. Search the scientific literature for suitable protocols and systematically test promising approaches to improve sample preparation. Learn
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: mathematics (algebra, geometry, probability theory, optimization theory), statistics, theoretical physics, theory of computation. Cutting-edge Disciplines: deep learning theory, generative models, graph neural
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School of Quantum at the University of Chinese Academy of Sciences (UCAS) | Spain | about 23 hours ago
Ph.D. or equivalent degree and have demonstrated ability to conduct outstanding research. Successful candidates are expected to carry out independent and innovative research, be able to teach both
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research environment. Personal Competences: We are looking for a proactive, organized, and collaborative person, with a genuine interest in people and strong motivation to learn and grow. Summary
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commitment to fostering a diverse and inclusive community in the practice and teaching of science. The successful candidates will be expected to have excellent academic achievements, teach graduate and
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: MSc in Physics, Materials Science, Nanoscience, Computer Engineering, Data Science, Gaming Engineering or a related discipline. · Knowledge: Strong coding skills in Python and knowledge in materials
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mandatory. · Personal Competences: We are seeking highly motivated, independent thinkers, who are well organised and willing to learn. Summary of conditions: Full time work (37,5h/week) Contract
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micro/nanofabrication techniques. 5) Contribute to the development of experimental instrumentation, automation routines, and laboratory infrastructure. 6) Acquire, organize, curate, and maintain
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Cluster hire of PIs and postdocs in the fields of evolution, biodiversity conservation and ecology, genetics, neuroscience, brain-computer interface, human disease mechanisms and Interdisciplinary