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for this job See advertisement About the position Position as PhD Research Fellow in Machine Learning is available in the Department of Informatics and the Norwegian Centre of Excellence Integreat . Starting
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materials science and engineering, manufacturing or other suitable engineering disciplines. Research experience in solidification and casting of metallic materials, and in-depth research knowledge and hands
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Experience and knowledge of the following is highly desirable : A Bachelor's degree in computer science with a background in NLP, a Bachelor's degree in (computational) linguistics or in symbolic systems A
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AUSTRALIAN NATIONAL UNIVERSITY (ANU) | Canberra, Australian Capital Territory | Australia | about 1 month ago
, School of Cybernetics, and School of Engineering, supported by the Professional Services Group. School of Computing - The School of Computing has a strong foundation in computing and information sciences
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. The successful candidate will become an active member of the Energy, Power and Intelligent Control (EPIC) research centre within the School of Electronics, Electrical Engineering and Computer Science (EEECS
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subject who have the ability to lead an exciting, innovative and fundable research programme. The applicant would typically have at least 3 years of post-doctoral experience and may already have experience
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conferences offered by the Reischauer Center. They are able to interact with senior researchers affiliated with the Center as part of our Visiting Scholars Program, who typically join us for one academic year
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teams to design, implement, and optimise innovative solutions that push the boundaries of technology. The role will span various stages of the project lifecycle, from initial concept development to final
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St Lucia location About This Opportunity We are looking for an exceptional Postdoctoral Research Fellow to join the Scanning Probe Microscopy and Materials for Quantum Technology (SPMQT) Lab
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: • PhD (or nearing completion) in optics, photonics, physics, electrical engineering, or a related field. • A record of high-quality publications with evidence of contribution to the writing