54 evolution "https:" "https:" "https:" "https:" "https:" "Here We Are" PhD positions at University of Nottingham
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datasets, and large-scale statistical studies comparing different methods. The successful candidate will be jointly supervised by: Dr Edward Gillman (https://www.nottingham.ac.uk/physics/people
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, preferably at Masters level (in exceptional circumstances a 2:1 degree can be considered). To apply visit: http://www.nottingham.ac.uk/pgstudy/apply/apply-online.aspx For any enquiries about the project please
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to predict the common distortions that occur when imaging into plant roots. From here we can either correct for these distortions using the hardware in the microscope or in software using reconstruction
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engineering, structural, aerodynamic & manufacturing process modelling and optimisation techniques that will transform current design & development practices. Together we will make technological advances
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sustainable chemical and biocatalytic process development. Vision We are seeking a motivated PhD student to develop a strong experimental understanding of enzyme selectivity when processing mixed biomass
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Turbulence detection in blood flow using 4D MRI Flow disturbances in blood flow are vital sign of cardiovascular diseases, suggesting a development of turbulent flow due to abnormal heart movement
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to the development of future manufacturing systems that are robust, reconfigurable, and fit for long-term operation. Motivation Modern manufacturing systems are required to operate under increasing uncertainty
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chemistry, flavour analysis, rheology, sensory science, and data-driven modelling, alongside structured development in responsible AI use, industry-relevant decision making, and translational research
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to cover living costs; Join a multidisciplinary cohort to benefit from peer-to-peer learning and transferable skills development. Learn more about the programme, available projects, and the application
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functional theory. In collaboration with Phasecraft, a leading quantum algorithms company, this project will explore the generation of new quantum computing datasets and the development of machine learning