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Field
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research, covering research topics including, but not limited to Crop Modeling, Machine Learning, Artificial Intelligence (AI), Internet of Things, and Big Data analysis for Precision and Prescriptive
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modeling. Brief Description of Duties: The Postdoctoral Associate will assist the Principal Investigator Dr Fang Luo in the Department of Electrical and Computer Engineering . The incumbent will conduct
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trustworthiness modeling on multimodal data and machine learning models. The Department of Computing Science has been growing rapidly in recent years, with a focus on creating an inclusive and bottom-up driven
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and trustworthy machine learning-based clinical prediction models. Funded by the Medical Research Council (MRC) and the National Institute for Health and Care Research (NIHR), the project aims
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candidates with a proven track record in developing open-source machine learning, deep learning, or cheminformatics tools (Preferred written in Python). Job Duties Plans, directs and conducts research
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, applications of machine learning to particle phenomenology, and lattice QCD, both within the Standard Model and beyond. The particle physics phenomenology group members are: J. F. Kamenik (head), B. Bajc, S
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. Department Specific Functions Research and Development: Develop and apply AI and machine learning models to analyze large-scale cancer datasets, including genomics, transcriptomics, and proteomics data. Data
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Designing and extending algorithms grounded in probabilistic machine learning Applying statistical techniques to assess robustness and generalization. Development of methods of research, testing and data
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biology, epidimological data and AI-driven systems modeling. The successful candidate will develop and apply computational and machine learning approaches to decode the molecular and epigenetic mechanisms
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the next generation of PV technologies for beyond 2030. The new postdoctoral research position will use materials modelling techniques (DFT, molecular dynamics, machine learning potentials) to investigate