324 programming-"Multiple"-"U"-"Prof"-"O.P"-"Humboldt-Stiftung-Foundation" "U.S" PhD positions in United Kingdom
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An exciting opportunity has arisen for two Research Assistants (RAs) within the Institute of Mental Health. The RAs will be working on the ESRC/NIHR funded DETERMIND programme (www.determind.org.uk
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based modelling, the application of mathematical concepts from UQ/ML to practical problems, and an understanding of scripting/programming. Individuals with an applied mathematics background who have an
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temperature stability and spatial resolution, to make a leap in this field. The PhD research programme will squarely address these challenges. The PhD candidate should have completed (or about to complete
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environments—such as fleets with multiple aircraft types. Objectives Objective 1: Map current data types, structures, and interoperability challenges to build a detailed "as-is" understanding of current
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requirements for our PhD programme . Candidates should have a strong background and first degree in chemistry or pharmaceutical sciences or a closely related subject (BSc/MChem/MSc). Industrial experience
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requirements for our PhD programme . Candidates should have a strong background and first degree in chemistry or pharmaceutical sciences or a closely related subject (BSc/MChem/MSc). Industrial experience
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work on the INSTINCT-MB programme, which brings together teams based at Newcastle University, The Institute of Cancer Research and University College London. The programme will generate a wide range of
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to the launch of the Bloomberg Cambridge University Corporate Bond Index later in 2025 and the delivery of the ongoing research programme related to the index project. The successful candidate will undertake desk
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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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powerful framework for decentralised machine learning. FL enables multiple entities to collaboratively train a global machine learning model without sharing their private data, thus enhancing privacy