410 genetic-algorithm-computer "Integreat Norwegian Centre for Knowledge driven Machine Learning" Postdoctoral positions in United Kingdom
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based on the understanding that early experience shapes the way our brain is constructed. While the “ground plan” of the brain is genetically determined, it is also influenced by environmental experience
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shelves, the breakup of which can speed up flow of grounded ice and affect global sea level, and on the highly specialised Antarctic biodiversity. This ambitious programme brings together leading UK (BAS
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disease activity. This is an excellent opportunity to contribute to a collaborative research program dedicated to improving our understanding of ALS and informing future clinical trials. You'll also benefit
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and statistical modelling, statistical image analysis and computer vision, chemometrics, biophysics, bioengineering. Preference will be given to candidates with a demonstrated experience in applying
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are seeking to appoint a postdoctoral research associate as part of a UKRI Future Leader Fellowship funded research programme. The successful candidate will work as part of a team to develop and apply deep
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have completed, or be close to completing, a PhD/DPhil in a relevant quantitative field such as computational social science, computer science, or cognitive science. They will have a demonstrable track
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are seeking to appoint a postdoctoral research associate as part of a UKRI Future Leader Fellowship funded research programme. The successful candidate will work as part of a team to develop and apply deep
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of climate science, statistical methodology, and computational modelling. The PROTECT project is part of the ARIA-funded programme on climate tipping points and aims to improve the scientific and statistical
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. To discuss the post in more detail, please contact Dr Carla Solorzano-Gonzalez, Senior Programme Manager, using the contact details : carla.solorzanogonzalez@paediatrics.ox.ac.uk Only online applications
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About the Role The project “An Erlangen Programme for AI” (funded by the UKRI), will broadly involve applying advanced mathematical techniques for understanding training in neural networks, with