18 algorithm-development-"Multiple"-"Simons-Foundation"-"Embry-Riddle-Aeronautical-University" "Prof" Fellowship positions at University of Leeds
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your career in one of the UKs leading research-intensive Universities? Based in the laboratories of Prof Stephen Muench and Dr Charlie Scarff at the Astbury Centre for Structural Molecular Biology, you
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Mamatha Nagaraj, Prof Helen Gleeson, Prof Gordon Love, and Dr Richard Mandle and at the University of Leeds. You will have an experimental PhD degree (or have submitted your thesis before taking up the role
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Mamatha Nagaraj , Prof Helen Gleeson , Prof Gordon Love , and Dr Richard Mandle and at the University of Leeds. You will have an PhD degree (or have submitted your thesis before taking up the role) and
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? Do you want to develop your career in one of the UK’s leading research-intensive Universities? We are looking for an enthusiastic and agile post-doctoral Research Fellow to work on the Healthy Low
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decision making, while you will be capable to apply machine learning and computational algorithms of social choice. This post is associated with following projects: Embedding EDI in the Distribution
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the climate crisis while also demonstrating a strong background in communicating evidence and insights to multiple stakeholders. Please note that this post may be suitable for sponsorship under the Skilled
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). This role is an exciting opportunity to take a role in the development, management and analysis of a new repository of Individual Participant Data (IPD) from ageing research trials. The work is an
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flows, using data on e-mobility demand, traffic and parking patterns, and grid configuration. This work will contribute to the development of statistical models to predict and support power supply
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patient safety. Our methods include: systematic literature reviews; qualitative, quantitative and mixed methods studies; complex intervention development; evaluation of interventions, including trials. We
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this role, in collaboration with BorealBlaze Norwegian and other international partners, you will apply machine learning methods to develop a statistical model of natural and anthropogenic controls on boreal