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Field
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Applications are invited for a PhD project within the University of Nottingham’s Faculty of Engineering, in the Centre for Additive Manufacturing research group (CfAM). The student will work in
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participate in the dissemination of findings through publications and conferences. Qualifications: Completed or nearing completion of a Master's degree in Medicinal Chemistry, Chemical Engineering, or a related
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, with minimal computational cost. By developing an advanced reduced order modelling framework, this project will empower engineers and designers to achieve more with less—delivering high-impact decisions
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the PhD in Engineering programme. Make sure to reference the supervisor's name (Dr Farzad Hayati) in your application. Informal enquiries are welcome and should be directed to Dr Farzad Hayati at f.hayati
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challenging properties of uncertainty, irregularity and mixed-modality. It will examine a range of models and techniques that go beyond Markovian approaches, including state-space models, tensor networks, and
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The funding provider: Health Data Research UK Subject areas: Wider Data Science Field, Maths and Computer Science Project start dates: 1st October 2025 ** (Please see the note below regarding
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begore the deadline. The start date is 1st October 2025. This studentship is related to a multi-institutional EPSRC Programme Grant "AMFaces: Advanced Additive Manufacturing of User-Focused Facial
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mixed-modality. It will examine a range of models and techniques that go beyond Markovian approaches, including state-space models, tensor networks, and machine learning frameworks such as recurrent
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, requiring large computational effort to assess and study system stability. This is becoming even more challenging under increasing complexity requiring detailed dynamical models and with new dynamic phenomena
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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