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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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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
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role in the development of testing rig setups and the modification/re-purposing of existing rigs and equipment. Common activities include machining, cutting, water-jetting, welding, assembling and
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++, Python, LabView) and firmware development. Working experience with IoT, data analytics, artificial intelligence, machine learning, etc. Working experience with various development boards systems like
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rig setups and the modification/re-purposing of existing rigs and equipment. Common activities include machining, cutting, water-jetting, welding, assembling and working with cabling and hydraulics
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to continuous improvement. Contribute to the development of appropriate programmes, modules and lectures in accordance with academic and military learning objectives. Participate fully in assessment
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. • Contribute to the development of appropriate programmes, modules and lectures in accordance with academic and military learning objectives. • Participate fully in assessment and examination processes as
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an exciting opportunity to a graduate with the relevant skills and knowledge to develop and implement machine learning techniques to derive new-to-sector advanced insights from Aids to Navigation maintenance
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analyses, and machine learning approaches that link genotype, primarily genome sequence data, to phenotype. A key focus will be developing models to predict the potential threat of various strains to human
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Design of a Fault Detection System for AI-Assisted Adversarial Attacks on Industrial Control Systems
AI-assisted adversarial attacks. You will work on topics such as cybersecurity, intrusion detection, adversarial machine learning, industrial automation, digital twin technology, and reinforcement