255 distributed-computing-"St"-"University-of-St"-"St" positions at University of Sheffield
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workflows, but also by helping to reimagine digital editions beyond the constraints of print-based models. In particular, it researches and analyses how computational and AI-driven methods, including but not
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collaborate with researchers at Ludwig Maximilian University, Munich and Centre Algatech, Trebon, Czech Republic, as part of the Synergy research programme. The aims of the Sheffield part of the Synergy
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Application/interview Good working knowledge of a relevant computer programming language, for example Matlab, Python or C/C++. Essential Application/interview Good working knowledge of software packages
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A search for pharmacological inhibitors of a cancer-associated adhesion GPCR in the zebrafish embryo
are seeking a motivated student with interests in developmental biology, disease modelling and drug discovery. This interdisciplinary project combines both wet bench work and computational work (bioinformatics
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/groups of students and programme directors. Undertake module evaluation, including facilitating student feedback, reflecting on own teaching design and delivery; and implementing ideas for improving own
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industry experts, gaining valuable skills at the interface of hydrogeology, environmental engineering, and computational modelling. Research Objectives will focus on: (a) Enhancing CoronaScreen by
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Improving Deep Reinforcement Learning through Interactive Human Feedback School of Computer Science PhD Research Project Directly Funded Students Worldwide Dr Bei Peng, Dr Robert Loftin Application
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contexts. The project will build on both consolidated knowledge in the history of technologies, and the most recent literature on the perception of digital and computer-assisted creative outputs
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, reactor design and computer programming. Entry requirements: Upper second class degree in Chemical Engineering, Materials Science and Engineering or Chemistry. Funding Notes Department contribution (fee
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-resolution imaging and reconstruction of neural tissues (see https://ist.ac.at/en/research/siegert-group/). Leveraging computational tools such as machine learning and topological data analysis, we will