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), or international equivalent, in Engineering, Computer Science, Physics or Mathematics with evidence of programming experience. Equality, diversity and inclusion is fundamental to the success of RAINZ CDT and is at
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), or international equivalent, in Engineering, Computer Science, Physics or Mathematics with evidence of programming experience. Equality, diversity and inclusion is fundamental to the success of RAINZ CDT and is at
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honours degree (2:1 with 65% average), or international equivalent, in Engineering, Computer Science, Physics or Mathematics with evidence of programming experience. Equality, diversity and inclusion is
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% average), or international equivalent, in Engineering, Computer Science, Physics or Mathematics with evidence of programming experience. Equality, diversity and inclusion is fundamental to the success
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Research theme: Formal Methods How many positions: 1 This 3.5 year PhD is funded by the Department of Computer Science at The University of Manchester. The successful candidate will receive
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Engineering, Environmental Engineering, Hydrogeology, Geosciences, Environmental Sciences, or related STEM disciplines (e.g., Applied Mathematics, Physics, Computational Sciences). Experience in numerical
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a variety of machine learning algorithms trained on these data and, most crucially, will develop and implement techniques for computing the uncertainty in the prediction. The algorithms developed in
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have a 1st or high 2:1 degree in electrical/mechanical engineering, physics, mathematics, or related disciplines. Skills in numerical tools and programming are desirable. Any experience in engineering
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) at the master’s level (at least a 2.1 honours) in a relevant science, mathematics, or engineering discipline are especially encouraged to apply. Additional requirements: Demonstrated determination and resilience
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a variety of machine learning algorithms trained on these data and, most crucially, will develop and implement techniques for computing the uncertainty in the prediction. The algorithms developed in