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sensitive to malicious deviations while remaining resource efficient. Solutions must operate effectively on network gateways or even capable IoT devices. The research will investigate statistical methods
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algorithms. Graph Neural Networks. The candidate is expected to hold a relevant MSc degree in Computer Science, Data Science, Physics, (Applied) Mathematics, Computational Statistics or another field
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and develop advanced cryogenic power electronics solutions for key net-zero applications such as all-electric aviation and wind energy. This fully-funded PhD project will provide the opportunity
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a strong career-defining network. The IntelliWind Doctoral Network provides training for a new creative, entrepreneurial, innovative, and resilient industry-oriented academic generation ready to face
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for advanced courses, international research visits, and networking across Sweden’s top universities. Information about the research group The Computer Vision Group at the division of Signal processing and
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. Experience writing project proposals. Experience in tomography analysis for 3-D imaging. * Significant experience is defined as two (2) to five (5) years of experience. Condition of Employment Reliability
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software. The TELOS collaboration, co-led by researchers at Swansea University and The University of Edinburgh, and with links in other Institutions in the United Kingdom, Taiwan, Korea, Austria and Japan
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cases. Additional engagement with other organisations may also be part of the research journey, providing exposure to a broad network of practitioners and stakeholders. Funding and Eligibility Fully
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challenging. Characterising the mechanical behaviours of thin foils at elevated temperatures is crucial in defining the load capability of aerostructures during the forming and joining processes. This PhD aims
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-based metadata platform that you will help develop. In collaboration with stakeholders from energy research, you will develop methods to increase data and software interoperability, enabling the automated