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machine learning. Colourbox via Unsplash Colourbox What skills are important in this role? The Faculty of Mathematics and Natural Sciences has a strategic ambition to be among Europe’s leading communities
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supportive team culture To learn more about the social atmosphere and team philosophy, please visit our website www.quantumcrew.org Qualifications PhD in experimental physics in a related field (quantum optics
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for Catalysis and Organic Chemistry at the Department of Chemistry. The group has extensive experience in computational modelling, reaction mechanisms, and machine learning for catalyst design and discovery. Nova
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with machine-learning–enhanced statistical inference. This position is based at the University of Otago in Dunedin and will be managed/supervised by Dr Fabien Montiel. The postdoctoral fellow will lead
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for this position, the following is required: PhD in data or computer science, machine learning, AI, statistics, mathematics, biophysics, bioinformatics. Additional requirements In addition to your CV and your
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English PhD Research Fellow in statistical population ecology Apply for this job See advertisement About the position A 4-year position as PhD Research Fellow in statistical population ecology is available
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diverse workforce is key to the successful pursuit of excellence in research, innovation, and learning for all faculty, staff and students. Our commitment to employment equity helps achieve inclusion and
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on the developed models for agencies/commercial partners Supervise junior researchers and master students Job Requirements: Preferably PhD in Computer Engineering, Computer Science, Electronics Engineering or
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conferences in areas of machine learning, computer vision, and Large Language Models and high-impact specialist peer reviewed academic journals. • Ability to conduct interdisciplinary research activities
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. To perform any other duties related to the research program. Job Requirements: Preferably PhD degree in Computer Engineering, Computer Science, Electronics Engineering or equivalent. Independent, highly