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Field
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an exciting, emerging topic. The position will focus on integration and device fabrication based on combinations of 2D materials and freestanding complex oxides, aiming at discovering, engineering and unlocking
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Recruitment Seek PhDs skilled in data mining, AI, nano-optics, and protein-structure analysis Preference for candidates with multi-disciplinary or industry–academia–research collaboration experience Development
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Information Theory. While excellent candidates with other research interests might be considered, priority will be given to those able to relate to one or more of the above topics. Applicants must have a PhD in
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The Faculty of Engineering, Department Elektronica en informatica, research group Electronics and Informatics: Research – Development - Innovation, is looking for a postdoctoral researcher. More
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software Writing reports and research articles where you will be co-author. Your qualities You hold a PhD (or are close to submission, or have recently submitted) in statistics, data science, or a related
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papers and presenting work at seminars and conferences. Required Knowledge, Skills, and Abilities: PhD in physical chemistry, or a related field. Preferred Knowledge, Skills, and Abilities: Experience in
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Associate: A PhD (or equivalent) in an area pertinent to the subject area, i.e. Computer Science, Machine Learning, Robotics. Research Assistant: A Master’s degree (or equivalent) in an area pertinent
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We are seeking a full-time Postdoctoral Research Assistant to join the Torr Vision Group at the Department of Engineering Science, central Oxford. The post is funded by Toyota Motor Europe and is
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. Qualifications and Experience possess a PhD in Computer Science, Robotics, Mechatronics, Biomedical Engineering, or a related discipline; demonstrate strong programming proficiency in C++ and/or C#, with a solid
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across domains. The research unit Intelligent Systems (IS) in Computer Science is focused on the development of Data Science, Pattern Recognition and Machine Learning algorithms for interdisciplinary data