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Field
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qualifications As our new colleague in our research team your job will be to develop novel computational frameworks for machine learning. In particular, you will push the boundaries of Scalability, drawing upon
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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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Mathematics or in mathematical aspects of Computer science, with excellent results. Start in or around September 2025 ; an earlier or later starting date is possible. The Mathematics department offers
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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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a doctorate. We are looking for: candidates with a Master’s degree in mathematics or a closely related field and with a strong background in probability theory. Prior knowledge in spatial stochastic
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Honours degree (or equivalent) in an appropriate discipline such as Computer Science or Mathematics. Applicants are expected to have excellent mathematical skills as well as an interest in discrete
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journals Your Profile: Master’s degree in soil chemistry, bioengineering, biochemistry, bioinformatics, or applied mathematics Hands-on experience in using differential calculus Solid knowledge in soil
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boundaries. This fully funded PhD scholarship is suitable for students with a background in Engineering Design, Smart Manufacturing, Aerospace Engineering, Mechanics, Computer Science, Mathematics, Life Cycle
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should have or expect to achieve, at least a 2:1 (or equivalent) in any engineering degree programme, physics or mathematics. English language requirements: Applicants must meet the minimum
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science, computer science, applied mathematics or a related field a strong background in machine learning, material modeling, and metals processing, modeling and simulation (This will be a clear advantage