46 parallel-computing-numerical-methods-"DTU" PhD positions at University of Nottingham in United Kingdom
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methods including quantitative, qualitative and health economic approaches. Informal enquiries may be addressed to the Nottingham MHM programme lead for mood disorders and lead supervisor of this PhD: Dr
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into hydrogen and nitrogen under practical onboard conditions. Successful candidate will develop and apply computational methods, such as density functional theory based atomistic modelling and machine learning
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, organisational and policy context of the National Health Service. The PhD research will focus on how bottom-up networks are involved in promoting change. In recent years, numerous networks of clinicians
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to characterise the material behaviours of thin sheets and foils (tensile, shear and creep effects) to improve the forming process and optimise process variables. Experimental methods for testing mechanical
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engineering. Expertise in numerical tools (Ansys, JMAG, .etc) and programming are desirable. Experience in electrical machine prototype development would be advantageous. Eligibility and Application
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, or related disciplines. Skills in numerical tools and programming are desirable. Any experience in engineering design or manufacturing would be advantageous. Eligibility and Application Due to funding
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Applications are sought for a fully-funded 42 month PhD studentship to work with Dr Rachel Nicks and Prof Stephen Coombes on the project: White Matter Computation: Utilising axonal delays to sculpt
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(School of Computer Science) External Partner: Build Test Solutions Ltd (BTS) Start Date: 1st October 2025 Eligibility: Home students only | Minimum 2:1 in a relevant discipline Stipend: Home students only
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Mechatronics/ Robotics/ Mechanical/ Computer Science or related scientific discipline. Outstanding analytical and numerical skills, with a well-rounded academic background. Demonstrated ability to develop
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repair and maintenance of gas turbine engines. Applicants are invited to undertake a fully funded three-year PhD programme in partnership with Rolls-Royce to address key challenges in soft robotics