18 development-"https:"-"https:"-"https:"-"https:"-"https:"-"https:"-"https:" PhD positions at The University of Manchester
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of developing low-risk, high-performance geothermal energy solutions. The PhD will examine high-density polyethylene U-tube systems suspended in minewater voids, focussing on: i) their comparative performance
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safety concern: they can generate significant heat and damage, critically compromising system redundancy and operative ability. This PhD combines industrial and academic expertise to develop next
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simultaneously developing the skills, experience and profile required for a future career in academia. You’ll leave with both a PhD and training in higher education teaching with the opportunity for accreditation
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computational fluid dynamics (CFD) simulations of blood flow through arteries and develop a cutting-edge super-resolution framework using convolutional neural networks (CNNs). The ultimate goal is to vastly
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removed before the deadline. This PhD will develop AI-enhanced flexible antenna systems for resilient next-generation wireless networks. By exploiting flexible antenna technologies, the project will
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will develop nanoscale devices which use magnons (collective excitations in magnetic order) as information carriers for ultra-efficient, compact, brain-inspired computing. This project is positioned
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of biomimetics by developing artificial nanochannels inspired by biological mechanosensitive receptors. With a focus on mimicking the exquisite touch, force, pressure, and nuanced responses to various physical
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) synthetic scope of these reactions; (2) use of synthetic enzyme cofactors to enable the oxidation of a wide range of quinoid species; (3) directed evolution of enzymes towards high value target compounds. In
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the deadline. The project topic is flexible and will be developed jointly by the student and the supervisor, depending on the candidate’s background and research interests. Possible directions include 3D body
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structures may change with time, where the change can depend on latent factors or variables. These projects will focus on developing a comprehensive Bayesian learning framework for this broad class of problems