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Statistics for Cybersecurity

  • Full or part time
  • Application Deadline
    Applications accepted all year round
  • Funded PhD Project (Students Worldwide)
    Funded PhD Project (Students Worldwide)

Project Description

Cybersecurity is a vast area and touches both on offensive as well as defensive techniques. An overarching theme though is the concern of information leakage from a system: statistics (and other data science as well as machine learning) tools are of great interest to detect and quantify information leaks.

The Cybersecurity Research group at AAU has been newly established by Prof. Elisabeth Oswald, whose interest is that of finding and eliminating such information leaks in the context of embedded devices (they often exhibit a number of so called side channels). In this particular setting, Elisabeth has successfully used and further developed statistical techniques (both for spotting such side channel leaks as well as characterising and understanding them). For her work in this area Elisabeth received a number of awards, the lastest being an ERC CoG grant. The successful applicant would work closely with Elisabeth and would develop into an applied statistician with a profound understanding of the application thereof in the area of Cybersecurity. The focus of this studentship is on the use of statistical techniques in the context of information leakage from side channels.

The student will be embedded in the Cybersecurity research group, which currently consists of one further lecturer, two postdocs, and two further incoming PhD students who work in the areas of crypto, statistical machine learning, embedded security, AI and deep learning and crypto engineering. There will be opportunities to get involved in teaching.

If you consider applying please send an email to the provided address which contains a brief description of why you think you would be suitable for this position, your CV, your recent transcript(s), and if your MSc thesis is in English an electronic copy of it. I will consider applications as they come in (I will reply to your email if your application fulfills the brief with an invitation to a Skype interview), and fill the vacancy as soon as a suitable candidate has been identified.

Funding Notes

The position has funding for 40 months. The successful applicant is expected to start as soon as possible. The PhD programme at AAU requires doing some taught modules, but is otherwise entirely research lead. You must possess a Master's level qualification (a BSc is not sufficient). Applicants with a strong background in statistics will be preferred but applicants with some background in statistics and/or machine learning will be considered.

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