55 phd-studenship-in-computer-vision-and-machine-learning PhD positions at University of Nottingham
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We are inviting applications for a fully funded PhD place, which will be supervised by Dr Joanne Cormac of the University of Nottingham's Music Department, for three years, starting on 1 October
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Technology, The University of Nottingham. Applicants are invited to undertake a three-year PhD programme in partnership with industry to address key challenges in on-platform manufacturing engineering. The
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photonic design software (Lumerical, Comsol, MEEP or HFSS) will be an advantage. A solid understanding of electromagnetics, mathematics and statistics, and machine learning theory/algorithms, with excellent
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combination of academic and industrial challenges which will enhance the student’s ability to tackle complex intellectual and practical aspects of computer vision and robotics. We are seeking talented
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suitable for a hard-working researcher with an interest in respiratory infections. Essential skills: A BSc degree or equivalent ideally in a health related field, excellent computer literacy, good inter
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English language proficiency proof (if applicable). After discussion, you may be invited for an interview. What the PhD Programme Offers: This PhD will include the payment of Home tuition fees as
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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
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Digital-Twinning of Electric Propulsion Systems Applications are invited for the above multiple research studentships to join the Power Electronics, Machines and Drives Research Group
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Applications are invited to undertake a three-year PhD programme in partnership with industry to address key challenges in manufacturing engineering. The successful candidate will be based
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groups: Cyber-physical Health and Assistive Robotics Technologies Computational Optimisation and Learning Lab Computer Vision Lab Cyber Security Functional Programming Intelligent Modelling and Analysis