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of optimization and generalization to inform the design of practical training algorithms. To produce high-quality publications in top-tier machine learning conferences and journals. To offer guidance and assistance
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Applicants are invited for a PhD Fellowship/Scholarship at Graduate School of Technical Sciences, Aarhus University, Denmark, within the Civil and Architectural Engineering programme. The position
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Degree in engineering, computer science, physics, mathematics, statistics or related quantitative discipline (UK 2:1 or equivalent). Working understanding of modelling, machine learning techniques and
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geophysical survey and machine learning algorithms. Mainly responsible for processing geophysical/geomechanical data and analysing the data using machine learning. Conducting research, supervising undergraduate
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is developing research excellence in areas including Machine Learning, Big Data, Visual Analytics, Computational Intelligence, Machine Learning, Software Implementation and Testing, and their
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learning or other relevant disciplines. Mandatory for Academic Level B appointment: PhD in robotics, machine learning or other relevant disciplines. Please Note: Appointment to this position is subject to
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robotics, machine learning or other relevant disciplines. Mandatory for Academic Level B appointment: PhD in robotics, machine learning or other relevant disciplines. Please Note: Appointment to
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, combining experimental photonics with numerical modelling and modern machine-learning and optimisation techniques. The research will include coherent beam combination, programmable beam shaping, optical
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UiO/Anders Lien 16th October 2026 Languages English English English PhD Research Fellow in Machine Learning and Statistics Apply for this job See advertisement About the position Integreat
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background in geomodelling, geophysical and geotechnical investigation, geomechanical engineering, and machine learning. You will be expected to work effectively on a geophysical/geomechanical project, to