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. Experience with bioinformatics tools and libraries for genomics analysis (e.g., Seurat, Scanpy, CellRanger, Nextflow, Singularity, Docker). Expertise in machine learning techniques and deep learning frameworks
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Chain Analytics, including mathematical modelling, optimisation, and/or machine learning, and/or decision sciences. Advanced expertise in developing supply chain solutions using Python, optimisation
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, biomedical instrumentation, wearable technologies, biomedical integrated circuits and sensors, neural engineering, optogenetics, and medical machine learning. Quantum Engineering: quantum sciences 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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achieves shared goals and objectives. An in-depth knowledge of Supply Chain Analytics, including mathematical modelling, optimisation, and/or machine learning, and/or decision sciences. Advanced expertise in
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languages (C, C++, C#, Python, Matlab), experience with machine learning in robotics or computer vision, a desire to advance resilient, introspective processing architectures in robotics, a desire to work
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using AI and machine learning in developing new tools for better management of TIC members transformer fleets. Guided by experienced academic staff and supported by Industry experts through the TIC
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health courses, ensuring high-quality, place-based learning experiences. Additionally, you will support the development of professional courses and work-integrated learning experiences, fostering evidence
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teaching and research portfolio. The School is at the forefront of emerging fields, including Artificial Intelligence, Machine Learning, Quantum Technologies, Energy Informatics, and Immersive Technologies
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member and contribute to team development Understanding of spatial multiplexing technologies desirable Experience in analysis of pipelines leveraging Machine Learning/AI desirable Experience in the wet-lab