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on a new project called TRUSTLINE, which is part of the Learning Introspective Control (LINC) DARPA Program. The project aims to develop machine learning (ML)--based introspection and monitoring
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the delivery of the school’s learning and teaching outcomes, including working with conventional machine tools/hand tools within an Engineering Machine Shop environment. Ability to use good
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have forged a formidable history. As a teaching-intensive University, our courses are rooted in practice-based learning, and we provide wider support that sets our students up to succeed after graduation
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malignant precancerous lesions in the mouth. To facilitate the machine learning model building, the virtual oral tissue models will be developed based on knowledge derived from tissue-engineered constructs
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omics data, digital pathology, using cutting-edge AI and machine learning approaches. You will play a critical role in developing sophisticated computational pipelines, integrating complex multi-omics
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relevant professional certifications would be advantageous. 10+ years of working experience, including at least 5 in Artificial Intelligence, Machine Learning, Analytics, or a related area.SIT Internal
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focus may be considered, but preference will be given to candidates with subject matter expertise in the following areas: disruptive technology and AI; Russian strategy and doctrine; military operations
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that are embedded into routine health systems and data dashboards used to guide policy decisions. This role sits at the intersection of generative machine learning, statistical inference, geospatial analytics, and
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of computational optimisation, machine learning, and experimental design of new chemistry. You will develop Bayesian optimisation and other active learning approaches for experimental design with a focus on real
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to have the following skills and experience: Essential criteria PhD (or near completion) in bioinformatics, computational biology, machine learning, or a related field Significant experience in the analysis