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are in particular targeting development of data-driven high-performance computing techniques for unbiased discovery of generative models & theory and algorithms for network inference with special reference
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collection methods. You’re skilled in developing computational models and deep neural networks that reflect principles of human cognition and brain function. Your academic record includes high-quality peer
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will primarily support the Head of School (Professor George Panoutsos, Chair in Computational Intelligence) and his research activities in the area of Machine Learning (ML) for Engineering, focusing
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lead to reductions towards the net zero target. The successful applicant is expected to have a PhD or other postgraduate qualification with experience in a relevant area of engineering or technology and
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The University of Southampton is committed to excellence in all we do, applying our insights and inventiveness to solve complex engineering and environmental challenges. As a world-leading, research
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structural engineering or mechanical engineering, received no later than 6 years before the initial appointment. Strong expertise in programming for approaches including, computational mechanics, finite
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Therapy, Computer Science, Engineering, Mathematics, Science, Physics, etc). Emerging track record publishing in high quality journals (e.g., Medical Physics, IEEE, etc.). Experience presenting at high
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within an industrial domain such as engineering, geoscience, or energy systems. Solid understanding of both foundational and philosophical aspects of ontology, as well as informatic and computational
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field (e.g., Medical Physics, Radiation Therapy, Computer Science, Engineering, Mathematics, Science, Physics, etc). Emerging track record publishing in high quality journals (e.g., Medical Physics, IEEE
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, supported by PEACEPLUS, a programme managed by the Special EU Programmes Body (SEUPB). The PEACEPLUS programme is co-funded by the European Union, the Government of the United