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), clinical trials, disease surveillance, and the use of novel methods including Bayesian network, machine learning, social network analysis and dynamic data visualisation tools. Further information is
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About the Role A fantastic opportunity has arisen for a Senior Research Fellow to join the Power Electronics, Machines and Drives Research Institute (PEMC) at the University of Nottingham and become
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Vision conferences, CVPR, ICCV, ECCV and peer reviewed journals. Minimum Qualifications: PhD in Computer Science or a related field obtained within the last five years. Strong skills in machine learning
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research interests in one or more of the following subfields: scientific machine learning, optimization, deep learning, uncertainty quantification, (Bayesian) inverse problems, reduced order modeling, high
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processing would be an advantage. Proficiency in statistical software (e.g., R, Python, SAS, or Stata). Experience with clinical informatics approaches (e.g., cluster analysis, machine learning, Bayesian
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the potential to impact on protected groups and take appropriate action. Desirable Skills: Experience with machine learning or natural language processing. Knowledge of econometric methods for policy evaluation
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workforce is key to the successful pursuit of excellence in research, innovation, and learning for all faculty, staff and students. Our commitment to employment equity helps achieve inclusion and fairness
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the University's research culture and collaborative profile. Qualifications: PhD in Computer Science/AI or a closely related field. Extensive research experience in machine learning, deep learning, and self
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area of expertise. You may be a great fit if: You are a passionate researcher with a PhD in Computer Science or a related field, experienced in machine learning for spatial data management, with a track
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variety of related subject including: Machine learning and deep learning techniques, preferably with a focus on generative models (e.g. GANs, VAEs, LLMs, VLMs,). Robust data analysis methods and tools