564 computer-science-intern-"https:"-"https:"-"https:"-"https:"-"Ulster-University" PhD positions in United Kingdom
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studentship funded by the School of Life Sciences and Diamond Light Source, starting on 1st October 2026 This PhD project offers a unique opportunity to join a highly interdisciplinary team at the forefront
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or international conferences or in peer-reviewed publications). For background information on this project, see: [1] 3D Printing of Biocompatible Supramolecular Polymers and their Composites, L R Hart, S Li, C
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Application deadline: 31/03/2026 Research theme: Biocatalysis and Protein Engineering Centre for Sustainable Synthesis – BioProcess How to apply: https://www.mib.manchester.ac.uk/research/centres
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expertise in programming (C++, Python), computer architectures and Deep Learning (PyTorch, TensorFlow). Exceptional international candidates may be eligible for a fee waiver (read the following section
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push the boundaries of IoT and edge computing but also position yourself as a future leader in MEMS technology and natural computing. Supervisors: Primary supervisor: Amal Hajjaj Secondary supervisor
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opportunity to develop skills in computational chemistry (catalyst/reagent design and mechanistic studies). The student will regularly attend organic problem classes, present their research at national
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qualification. Background knowledge and experience in engineering and computer science disciplines and in areas such as CFD post-processing (OpenFOAM), wind turbine renewable energy systems, big data management
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(both quantitative and qualitative methods), and gain experience in collaborative research of national and international significance. With the guidance and mentorship of experienced researchers
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are invited for a 3.5-year EPSRC funded UDLA PhD studentship. The studentship will start on 1st October 2026. Project Description Offshore solar energy is an emerging and highly promising technology for
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or international equivalent, in an appropriate subject. A further qualification such as an MRes is advantageous. · Interest/experience in mixed methods including qualitative research and data science