350 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "https:" "UCL" "UCL" PhD positions in United Kingdom
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, including but not limited to computer science, data science, engineering or mathematics, who are passionate about machine learning and AI research. Strong analytical thinking, problem-solving skills, and the
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of the Manufacturing Technology Centre (MTC) and academics within the Power Electronics, Machines and Control (PEMC) Research Institute , University of Nottingham. The project will be supported by the state-of-the-art
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the intersection of ecology, machine learning, and sustainable land management, the research will combine field data collection, deep learning model development, and stakeholder co-design to support biodiversity
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. Be part of a diverse and active cohort working on and learning about data visualizations through research. Complete research-in-practice internships with academic and industrial partners across public
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have at least 2:1 degree in a relevant field. Applicants with the prior knowledge and experience in one or more of the following fields are encouraged to apply: computer programming (any programming
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signatory of the Armed Forces Covenant . an accredited Disability Confident Leader ; autism friendly university , committed to building disability confidence and supporting disabled staff .
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machine learning and AI research. Strong analytical thinking, problem-solving skills, and the ability to engage with complex data challenges will be greatly valued. Experience with Python or AI frameworks
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that will consider the electromagnetic aspects, through computer modelling and simulation, and then identify material systems that enable the design and manufacture of antennas for test and characterisation
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of the Manufacturing Technology Centre (MTC) and academics within the Power Electronics, Machines and Control (PEMC) Research Institute , University of Nottingham. The project will be supported by the state-of-the-art
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is advantageous but not mandatory—an eagerness to learn and innovate is key! Full training will be provided. Why This Matters Efficient storage technologies are essential for a carbon-neutral future