48 machine-learning "https:" "https:" "https:" "https:" Fellowship positions in United Kingdom
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related to staff position within a Research Infrastructure? No Offer Description We are seeking to appoint a Postdoctoral Researcher for a three-year position in machine learning emulators of ice-ocean
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processes that use data-driven machine learning. Given the span of the IN-CYPHER programme, we are seeking multiple motivated research fellows. Unique in its scope, we are developing technologies that span
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research interests compatible with those of our current faculty in the following research groups: mathematical biology, mathematical and computational finance, numerical analysis, machine learning and data
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of manufacturing. We have identified an opportunity to combine continuous microfluidic (µF) process models, process analytical technology (PAT) and machine learning (ML) to achieve a paradigm shift in bioprocess
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of manufacturing. We have identified an opportunity to combine continuous microfluidic (µF) process models, process analytical techn ology (PAT) and machine learning (ML) to achieve a paradigm shift in bioprocess
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of manufacturing. We have identified an opportunity to combine continuous microfluidic (µF) process models, process analytical techn ology (PAT) and machine learning (ML) to achieve a paradigm shift in bioprocess
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unique combined system using an optimised AF scanning procedure that integrates Raman measurements to analyse lymph node biopsies within 10 minutes and machine learning algorithms to deliver quantitative
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of subsurface processes. You will be responsible for leading the development of the approach, which could include transferring learning from other geographic regions and data types, machine learning methods
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therapeutic discovery and providing commercial growers sustainable methods to meet increasing global food demand. Responsibilities Apply machine learning techniques, statistical modelling, and chemometric
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proficiency in Python (e.g., NumPy, Pandas, scikit-learn, PyTorch, TensorFlow); additional experience with R, MATLAB, or Julia is an advantage. Machine Learning Expertise: Familiarity with supervised