17 software-verification-computer-science-"insights"-"Washington-University-in-St" Fellowship positions at University of Leeds
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resource consumption policies with both short term and long-term climate targets. With DESNZ funding 40% of the project, you will work directly with senior policy makers delivering actionable insights
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of the forecasts according to known physical drivers and constraints, such as tropical wave modes, feedback with the land surface and response to global sea surface temperatures. From these insights into climate
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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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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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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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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