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, complex omics datasets (e.g. transcriptomic, genomic, proteomic), with demonstrated skills in statistical modelling; experience in machine or deep learning is advantageous. Emerging track record of research
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, and building machine learning models for tasks like classification and regression Key responsibilities will include: Collaborate with Researchers and Students: Work closely with researchers and higher
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include, environmental hydrology and hydrogeology, environmental modelling, environmental impact assessment, land contamination and rehabilitation, pollution modelling and management, remote sensing
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-organised manner under pressure. Some experience in meaningful internal service roles and contributions towards external activities Desirable Knowledge/experience in large animal models Experience in
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meet the University’s business requirements. Demonstrated ability to design IT solutions within a large ERP platform, undertaking business process modelling, and data and systems documentation in
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models that help researchers detect change, assess trends early to support mitigation and adaptation strategies, and predict cumulative impacts of development. Join a community where excellence is at
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. An emerging research profile in the transformer condition monitoring discipline area including modelling, sensing, signal processing, and data analysing for transformer condition assessment. Evidence
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the design, modelling, layout, and verification of silicon/silicon nitride photonic devices to contribute to Process Design Kit (PDK) development, working closely with the Lead Process Engineer. Manage and
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variable models (e.g., CLIP, GLIP, MaskCLIP). Knowledge of Transferability in Machine Learning is desirable. Knowledge in Active Learning is desirable. Programming skills and experience with dataset
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to optimise research outcomes. Advanced Data Cleaning and Analysis: Clean,engineer, prototype, and deploy statistical and machine learning models using Python and/or R to solve complex problems; maintain and