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Field
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: Essential criteria MSc. in Neuroscience, Physics, Computer Science, or a related field Strong background in computational neuroscience and data analysis Proficiency in programming (e.g., Python, MATLAB, and
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Supervisors: Professor Richard Hague1 , Professor Chris Tuck1 , Dr Geoffrey Rivers1 (1 Faculty of Engineering) PhD project description: Inkjet printing allows multiple materials to be 3D-printed
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world-class laboratory facilities in the CfAM engaging with interdisciplinary team with expertise in 3D printing, biotechnology, physics, and materials science. PhD project description: Responsive 3D
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both homogenous and heterogenous catalytic conversion, including the handling, testing and characterizing the catalysts as well as the reactor and process simulation and analysis. Details will be
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used. AI methods for generating regulatory hypotheses between genes, hormones and physical properties will also be developed. Applicants must have/be close to obtaining a PhD or MPhil in Computational
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This 4-year PhD programme is fully funded for home students; the successful candidates will receive a tax free stipend based on the UKVI rate (£20,780 for 2025/26) and tuition fees will be paid
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measurement in construction. The skills, qualifications and experience required to perform the role are: Hold (or be close to obtaining) a PhD in Computer Science, Civil Engineering, Data Science, Information
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an appropriate subject (including Computer Science, Physics, Maths, Engineering) Knowledge of modern machine learning techniques and experience with coding in Python is beneficial (but not a strong requirement
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Applications are invited for a PhD project within the Faculty of Engineering, in the Centre for Additive Manufacturing research group (CfAM) at the University of Nottingham. The student will work in
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3-year PhD studentship: Scaling-Up Functional 3D Printing of Devices and Structures Supervisors: Professor Richard Hague1 , Professor Chris Tuck1 , Dr Geoffrey Rivers1 (1 Faculty of Engineering) PhD