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graduate training in mathematics, physics, computational sciences and related fields are strongly encouraged to apply; PhD research-equivalent MDs will be considered on a case-by-case basis). - Three years
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Criteria: A completed PhD (or very close to completion for Lecturer) in Finance/Financial Analytics or cognate disciplines. An established programme of research activity and dissemination of original, high
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their research communities, and to outreach activities that showcase research to the wider public. About the person: A PhD in Computer Science, Computer Engineering, Electronic Engineering (or related disciplines
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. Candidates must have: A PhD with a strong component in machine learning and deep learning (or a PhD defense planned for 2025), Research contribution in deep learning and application domains such as computer
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skills, with the ability to prioritize multiple projects, meet critical compliance deadlines, and maintain accuracy under pressure. Demonstrated adept research, investigative, and analytical abilities
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their research communities, and to outreach activities that showcase research to the wider public. About the person: A PhD in Computer Science, Computer Engineering, Electronic Engineering (or related disciplines
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its fellows in all areas. As the Georg Forster programme is intended to actively contribute to achieving UN Sustainable Development Goal 5 (gender equality), we particularly encourage women to apply. We
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specialising in interdisciplinary topics, for example, candidates specialising in Machine Learning and Data Science, Quantum Computing, Theoretical Computer Science, Financial and Actuarial Mathematics
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marketing plans for countries. Organize Student Faculty exchange programs: Invite the expression of interest from students and faculty for the program, select students and faculty for the program and aid in
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within units and guide students to appropriate support services where appropriate. To be successful, you’ll have: PhD in Information Systems, Business Analytics, or a closely related discipline Excellent