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optimization techniques, coding new algorithms, creating new mathematical theory, and the analysis of large data ensembles. You will write papers for submission to academic journals, collaborate with academics
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. We are looking for highly motivated candidates with a strong academic background in computer science, AI/ML, bioinformatics, or related fields such as mathematics and statistics. Informal enquiries
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mathematical training is essential, particularly the ability to understand and verify mathematical proofs. A clear motivation to pursue a PhD or an academic career in finance or economics is also required. Our
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Mathematics PhD on the Programme Choice page. You will be prompted to enter details of the studentship in the Funding and Research Details sections of the form. Candidate requirements: Applicants must hold
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model due to the mathematical challenge of solving the multiple partial differential equations simultaneously. With the support of the combined sponsorship from the university and industrial partner
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the development of new tools for coupled oscillator theory in time-delayed systems of differential equations. The resulting models will be analysed with analytical tools from applied mathematics and numerical
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level (or international equivalent) in a science, mathematics or engineering discipline. Applicants without a master's qualification may be considered on an exceptional basis, provided they hold a first
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PhD Studentship in Analysis of PDE Supervisors: Sugata Mondal Second advisor: Michael Levitin Project Overview: Spectral geometryis the area of mathematics where one studies inter-relations between
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, mathematics, engineering, computer science, or related subject) Proficiency in English (both oral and written). Knowledge in cryptography is desirable. Studentship and eligibility The studentship covers: Full
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AI-Driven Digital Twin for Predictive Maintenance in Aerospace - In Partnership with Rolls-Royce PhD
relevant field such as engineering, computer science, or applied mathematics. Experience or interest in AI, machine learning, or digital systems is beneficial. We welcome candidates from diverse backgrounds