638 phd-studenship-in-computer-vision-and-machine-learning Postdoctoral positions in Uk
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on understanding the spread and control of human infectious diseases using modelling and pathogen genomics. This is a short-term opportunity to apply machine learning methods to two key projects. First, you will
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also have or be close to completing a PhD in any of the following areas as well as the will and commitment to learn relevant topics from the other areas: Statistical and machine learning, mathematical
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are looking for candidates to have the following skills and experience: Essential criteria PhD qualified in mathematical, physical or computational sciences Experience in using machine learning methods
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intelligence; can present at national and international conferences; and prepare manuscripts as first or joint author for submission to leading journals and conferences in machine learning, cancer research and
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groups working on digital health and wellbeing , network science , computational social science , and various topics in machine learning. You will be working in the research group of one of the PIs
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state-of-the-art machine learning and deep learning techniques (such as generative adversarial networks), with empirical fieldwork in Norwegian glacier environments. As a Postdoctoral researcher, you will
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experts to acquire bespoke training and testing data; develop prototype solutions informed by the latest ideas in medical imaging AI, computer vision and robotic guidance; and evaluate models in simulated
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analysed by bespoke machine-learning driven algorithms, combined with physical models, to de-noise images, identify features and correlate properties, giving critical insights into power loss pathways
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this suits a candidate with a background in optical systems / imaging, or with more experience in machine vision, or systems control and automation, or data interpretation. A candidate would not be expected
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cytometry. Our experimental programme is designed to interface and synergise with simultaneous theoretical developments of computational models and novel methods for analysing system purposes