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(e.g., Reinforcement Learning, Agent Based Modelling) to join our team full-time as part of a large international collaboration of European researchers (incl. Tobias Dienlin, Veronica Kalmus, Adrian
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and motivated candidates for a postdoctoral positions working on cutting-edge research at the intersection of Machine Learning, Privacy-Enhancing Technologies, and Public Interest Technology. We
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-traditional, e.g., event data) and network structures (for sensor networks). In this project, we will investigate Bayesian deep learning approaches to training models under uncertainty for several sensing
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Postdoctoral Research Associate in Forest Resilience, Climate Change, and Human Health in the Amazon
illnesses. The post holder will also co-supervise a PhD student who will be involved in the same project. This is a highly interdisciplinary project combining forest ecology, remote sensing, machine learning
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matching post based at Teesside University); (3) nature and natural heritage (the focus of a matching post based at Newcastle University); (4) active evaluation for learning (e.g. research conducted by team
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ability to work co-operatively as part of a team. Experience of independently managing a discrete area of a research project would be desirable as would in setting up and managing learning platforms
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to quickly learn and independently apply new techniques.
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learning. The post-holder will be familiar with the use of these techniques and experience of dataset construction and data mining will be essential. The successful applicant will have completed an MPhil/PhD
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projects the Centre will be undertaking. This is an excellent opportunity to gain academic research experience and to learn from leading academics. The ideal candidate for this role will have a background in
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analysis and machine learning methods for optimisation and decision making, to describe the F&V supply chains for various products at regional UK scale and assess their resilience to cascading risks