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scholars in Law and two PhD students (one in Law and one in Computer Science/Data Analytics), as well as with international, European and national stakeholders involved in the CURE project. The post-holder
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also have or be close to completing a PhD in any of the following areas as well as the will and commitment to learn relevant topics from the other areas: Statistical and machine learning, mathematical
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, operations research, computer science, mathematical finance, or a related field, the successful candidate will demonstrate the ability to develop independent research ideas and contribute to advancing our
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/algebraic statistics in the School of Mathematics at the University of Edinburgh. The post is available from 1st September for a 36 months fixed-term, full-time contract with a potential 6 month extension
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capable of driving the project forward. The ideal candidate: The ideal candidate will possess (or soon complete) a PhD in Theoretical Physics, Bio-Mathematics or Computational Biology. They will possess a
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A position exists for a Post Doctoral Research Associate in the Department of Applied Mathematics and Theoretical Physics, funded by the High Energy Physics group's STFC Consolidated grant
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inference attacks, to mitigate privacy leaks in MMFM. You will hold a PhD/DPhil (or be near completion) in a relevant discipline such as computer science, data science, statistics or mathematics; expertise in
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://degradationproject.com/ ) and NEXGENNa (http://nexgenna.org/ ) projects and participation in regular relevant FI meetings. Applicants should hold (or be about to obtain) a PhD in Chemistry, Materials Science, or a closely
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://degradationproject.com/ ) and NEXGENNa (http://nexgenna.org/ ) projects and participation in regular relevant FI meetings. Applicants should hold (or be about to obtain) a PhD in Chemistry, Materials Science, or a closely
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of virus evolution into mathematical models of spillover infection and transmission of prototype viruses representing viral families concern to support the development of methods for virus sequence analysis