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the wind/renewable energy training and research elements of the CDT programme. Funded by Siemens Energy and EPSRC, this 4 year this PhD studentship, at the University of Strathclyde is in the area of
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, faster and more energy efficient data processing and storage. However, the heat produced by modern data centres has already become a serious limitation to further increase their performance. At present
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-efficient, flexible, and sustainable separation processes. However, their success depends critically on the discovery of high-performance sorbents that combine strong CO2 affinity with efficient
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, computer science, or a closely related discipline (typically first-class or high 2:1, or equivalent; Master’s welcome) • Strong programming skills (for example Python, MATLAB, C/C++) • Strength in at least two of
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on their staff. Our new grant funding will extend this programme to study how working time reduction could support employee inclusivity at work. In this grant-funded studentship, the PhD researcher will play a
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computational work involves protein structure prediction Publications in high impact factor journals Knowledge and experience in AMR, Artificial Intelligence in health and food systems Good laboratory skills
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their work at major international conferences. Applicants should have a 1st or high 2:1 honours degree (or international equivalent) in mathematics, physics, engineering, computer science or other related
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The project: The High Performance Computing (HPC) services of today provide the computational density to perform groundbreaking science. These services facilitate the distribution of a problem space
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channel. This will be followed by designing a new resilient waveform for UOWC and developing a computer-based simulation to evaluate its performance. Finally, the study will use existing UOWC channel
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, and flavin-dependent halogenases, to selectively modify three high-value natural products: Plumbagin – A naphthoquinone with potent anticancer activity. Lithocholic acid – A bile acid with emerging