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Digital manufacturing, Industry 4.0, or cyber-physical systems o Product design for disassembly, remanufacturing, or recycling o Data analysis, AI, or machine learning applied to engineering systems
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will be responsible for the follow : (full details of duties available from the Job Description) Research Collaboration and engagement You will have completed a PhD in machine learning, computer science
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AI and data science, particularly in dynamic settings where observations are collected sequentially and decisions influence future outcomes. This project will develop novel machine learning and
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. Applicants must have the right to work in the UK. We are unable to offer visa sponsorship for this role. Candidate requirements Candidates must have expertise in developing computer vision and machine learning
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discipline. Essential Good programming skills, preferably in Python/C#. Experience with machine learning, deep learning, or experimental AI evaluation. Interest in secure distributed AI, federated learning
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Join the Responsible Machine Learning (ML) Group at the Faculty of Computer Science. Led by Prof. Dr. Martin Pawelczyk, who recently joined the University of Vienna from Harvard University, our research
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automotive and aerospace electrification. Applications for this PhD position are invited at the Power Electronics and Machines Centre, University of Nottingham. Based in a recently built £18M facility
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for candidates with a background in or demonstrated ability to learn about: Bayesian methods, probabilistic machine learning or inverse modelling. Prospective applicants are encouraged to direct informal inquiries
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on clinical complications, and use machine learning to develop and validate predictive models to identify high-risk patients. The research aims to individualise inpatient care, reduce hospital-acquired
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backgrounds such as AI, computer vision, computer graphics, machine learning, robotics, wearable technologies, textile engineering, fashion technology, digital fashion, or related areas are encouraged to apply