17 software-verification-computer-science-"Prof"-"Washington-University-in-St" Fellowship positions at University of Leeds in United Kingdom
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Universities? You will join a collaborative programme with Merck Electronics KGa, a world-leading company working in liquid crystals. You will work with a team of scientists from the company along with Dr
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Studies and Academic Unit of Health Economics, the University of Southampton, University of Birmingham and University College London (UCL). The post has funding for 18 months full-time equivalent and we
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the role) in Computer Science/Electronic and Electrical Engineering or a closely allied discipline, you will have a background in cloud technologies for communication systems, and in programming with
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have a PhD or be a PhD candidate who has already submitted your thesis prior to starting the position, with a research track record on artificial intelligence, data science and computational social
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analysis of large datasets using statistical software. In addition, you will have excellent time management, planning, and verbal and written communication skills, with an aptitude for working with diverse
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This role will be based on the university campus, with scope for it to be undertaken in a hybrid manner. We are also open to discussing flexible working arrangements. Are you a Computer Scientist
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dynamics in the machine-learning predictions, we aim to understand drivers of predictability: are there “windows of opportunity” of high predictive skill which may benefit farmers? Please note that this post
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to Power Agriculture, Clean Cooking and Transportation’ project could be the job for you. Moving IMPACT is a £3.6m research project funded by the Engineering and Physical Sciences Research Council
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looking for your next challenge? Do you have a background in social science and higher education research? Are you interested in working in an interdisciplinary team to understand the impact of curricular
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the context of global climate change. The work will entail developing quantitative prediction models that will be integrated to wider health systems software for the predictions to be directly used for early