19 software-verification-computer-science Fellowship positions at University of Leeds
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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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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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Overview of the Role Are you an ambitious researcher looking for your next challenge? Do you have an established background in mechanosensing, engineering, or biomechanics? We are inviting
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will have or be close to obtaining a PhD in a relevant subject such as remote sensing, physics, mathematics, computer science or environmental science. Experience of processing satellite datasets
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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
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of Earth and Environment (SEE), and working closely with its School of Civil Engineering, you will use various seismic datasets – including data already recorded with fibre-optic distributed sensing systems