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the University’s/ Faculty’s/ Department’s approved PhD program and is expected to complete the project within the set fellowship period. The main purpose of the fellowship is research training leading
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requirements: PhD Degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, or a related field, obtained within the last five year Research Experience in one or more of the following
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physics models, Bayesian inversion methods, and machine learning algorithms in the electromagnetic context. Qualifications and personal qualities: Applicants must hold a master’s degree (or equivalent) in
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learning to model solid-state materials while collaborating with experimentalists. Qualifications • Ph.D. in Computational Physics/Materials Science, or related field (completed by start date
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must take part in the University’s/ Faculty’s/ Department’s approved PhD program and is expected to complete the project within the set fellowship period. The main purpose of the fellowship is research
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. The employment period will be three years of full time with no teaching obligations, and there is a premise for employment that the PhD Research Fellow is enrolled in USN’s PhD program in technology within three
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, and innovators to thrive in the digital age. Located in the heart of Asia, NTU’s College of Computing and Data Science is an ‘exciting place to learn and grow'. We welcome you to join our community
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of the following areas is an advantage: Modelling and simulations of flow in porous media. Programming, image processing and machine learning Personal and relational qualities will be emphasized. Motivation
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a PhD in Computational Biology, Applied Mathematics, Statistics, Biostatistics, Epidemiology, Bioinformatics, Computer Science, Neurological Genetics or a closely related discipline. Excellent oral
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written and oral English. Experience from one or several of the following areas is an advantage: Programming, image processing and machine learning. Magnetic Resonance Imaging. Laboratory experience from