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Northeastern University London Fully Funded PhD Scholarship in Computer Science Reliable Quantum Statistics Northeastern University London > Computing, Mathematics, Engineering & Natural Sciences
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biology or a quantitative discipline, such as physics, engineering or applied mathematics, with expertise in programming and an interest in developing AI-driven computational tools for biological data
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4-year PhD fellowship in the Research Programme - Deep Learning-Accelerated Crystallography Pipeline
determination by developing mathematical methods and integrating machine learning into crystallographic workflows. The successful candidate will develop theoretical and computational approaches to improve
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-year Computational Project to use state-of-the-art Computational Chemistry techniques to understand structure-property relationships in thermal batteries, and to derive new understanding to guide design
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This post (Research Assistant/Associate in Computational Methods for Structural Wing Design) will allow you to contribute to a major industry-funded project developing the next generation of
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only of storing information, but also of manipulating, organising, and retrieving it through molecular data structures analogous to those used in computer science. Building on our pioneering experimental
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awareness These funded PhD scholarships are suitable for students with a background in Computer Science, Mathematics, Engineering and Cognitive Science. Students with interests in machine learning, deep
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, a strong degree in computer science, cybersecurity, mathematics, or a related subject. Experience with cryptography, machine learning, or systems implementation is valuable, as are solid programming
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: 8856F Leave the 'Research Area' field blank Select ‘PhD in Process Industries; Net Zero (PINZ)' as the programme of study You will then need to provide the following information in the ‘Further Details
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at the intersection between computer science and condensed matter physics, offering the student the opportunity to work across both disciplines toward the development of next-generation computing technologies