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degrees in either the natural sciences (chemistry, physics, mathematical/computational biology) or in the formal sciences (statistics, computer science, mathematics), but must have a serious interest in
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programming, modelling, and data analysis skills. Experience with formulating and solving mathematical optimization problems is an asset. Proficiency in English is required; good comprehension and oral skills
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Spectral Theory" at the Mathematical Institute at the Georg-August University of Göttingen. Your profile Master degree in mathematics or equivalent Analytical profile with a research focus in harmonic and
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As a flagship research center in nanoscience and nanotechnology, our mission is to open and explore new frontiers of knowledge at the nanoscale, and bring value to society in the form of new understanding, capabilities and innovation, while inspiring and providing broad training to the next...
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Materials science and technology are our passion. With our cutting-edge research, Empa's around 1,100 employees make essential contributions to the well-being of society for a future worth living. Empa is a research institution of the ETH Domain. Per- and polyfluoroalkyl substances (PFASs) are a...
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Joint degree / double degree programme No Description/content Data Science is a scientific field that has emerged at the interface of computer science, mathematics, statistics and applications. It is
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: BSc, including mathematics, cell and molecular biology Honors (first class) or MSc degree in Microbiology/Immunology/Pharmaceutical Science, or related degree Accreditation in Laboratory Animal Science
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environmental and life sciences challenges. Courses will cover topics such as complexity science, mathematical modelling in evolution, ecology and plant biology, along with transferable skills, including
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dedicated PhD student with a 1st class or 2:1 degree in the field of Engineering, Mathematics, Physics, Architecture or Computer Science. A MSc degree in a relevant area is desirable though not necessary
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mathematical foundation of machine learning models. You will be responsible for developing scientific machine learning methodologies enabling new approaches for solving machine learning problems including