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a strong statistical, computational and mathematical background. The program features two curricula: Statistics and Computer Science. Candidates may apply either to a single curriculum or to both
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related discipline. This project would suit a candidate with a background in mechanical, control or aerospace engineering, physics, mathematics, or other relevant engineering/science degree. The ideal
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with algorithms for wearable data University of Manchester (UK): To learn mathematical modelling of hormone rhythms. University of Bristol (UK): To learn mathematical modelling of hormone rhythm
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health economics, labour economics, economics and econometrics. We will also consider other quantitative disciplines such as data science, mathematical statistics, actuarial science or public health
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mathematics Proficient in programming (Python and C++) Fluent in written and spoken English; knowledge of German is an asset Strong analytical and independent working style Excellent teamwork and communication
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Computer Science, Mathematics, or related areas. • Strong background in at least one of the following: formal methods, SMT solving, abstract interpretation, or model checking. • Experience with verification tools
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on advancing a broad spectrum of AI. The spectrum of available topics ranges from core areas of AI Theory, Hardware, Mathematic foundations, AI applications to societal aspects of AI. The topics are not limited
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/achieve a minimum of a merit at master’s degree level (or international equivalent) in a science, mathematics or engineering discipline. Applicants without a master's qualification may be considered
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a particular emphasis on embedded systems. About the organisation The faculty of Electrical Engineering, Mathematics and Computer Science (EEMCS) uses mathematics, electronics and computer technology
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honours degree in physics or a closely related discipline (e.g. applied mathematics, engineering physics, geophysics, astronomy/astrophysics), and have a strong academic record and clear motivation