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PhD studentship in Preserving Privacy in an Online World

  • Full or part time
  • Application Deadline
    Friday, April 17, 2020
  • Funded PhD Project (European/UK Students Only)
    Funded PhD Project (European/UK Students Only)

Project Description

One fully funded PhD position to work with Dr. Nadin Kokciyan in the School of Informatics at the University of Edinburgh, on a project titled “Preserving Privacy in an Online World”.

Overview of the Project

In online social systems, users are allowed to create and share content about themselves and others. The content being shared can affect anybody involved in it, and the privacy of individuals can be compromised. Increasingly, users need intelligent tools that can help them to manage their privacy online.

Existing work has shown that the use of AI techniques can reveal even more information about the content. For example, objects or faces can be automatically identified by machine learning algorithms. Or new information, such as the location information, can be inferred by the use of rule-based techniques.

The goal in this project is to build AI-based methods to preserve privacy in online social systems (such as social networks and IoT systems). This requires semantic representation of the domain (such as privacy preferences), detection and prevention of privacy violations, evaluating the developed mechanisms, and explaining privacy decisions to users.

It is expected that the candidate working on the project will work on both the theoretical foundations and the development of the privacy-preserving tools.

Candidate’s profile

• The project is suitable for a student with a top MSc or first-class bachelor’s degree in computer science, artificial intelligence, engineering, mathematics, or other related subject
• Strong analytical and programming skills
• Proficiency in English (both oral and written)
• Good understanding/knowledge/experience in at least two of the following areas: multi-agent systems, knowledge representation and reasoning, privacy, machine learning, natural language processing.

Application Information

Applicants should apply via the University’s admissions portal (EUCLID) and apply for the following programme: PhD Informatics: CISA: Automated Reasoning, Agents, Data Intensive Research, Knowledge Management - 3 Years (Full-time).

Applicants should state “Preserving Privacy in an Online World” and the research supervisor (Dr. Nadin Kokciyan) in their application and Research Proposal document.

Applications should be submitted by 17 April 2020, although complete applications received by 17 April 2020 will receive full consideration; after that date applications will be considered until the position is filled. The anticipated start date is flexible.

Applicants must submit:

• Degree transcripts and certificates (for both BSc and MSc if applicable)
• Evidence of English Language capability (where applicable).
• A short research proposal (max 2 pages)
• A full CV and cover letter describing your background, suitability for the PhD, and research interests (max 2 pages).
• Two references (note that it the applicant’s responsibility to ensure reference letters are received before the deadline).

Only complete applications will progress forward to the academic selection stage.

Environment

The School of Informatics is one of the largest in Europe and currently the top Informatics institute in the UK for research power, with 40% of its research outputs considered world-leading (top grade), and almost 50% considered top grade for societal impact. The University of Edinburgh is constantly ranked among the world’s top universities and is a highly international environment with several centres of excellence.

Funding Notes

The studentship starting in 2020/21 covers:

• A tax free stipend of GBP £15,000 per year for 3 years.

UK/EU applicants are eligible for this studentship. Exceptional OS students will also be considered.

How good is research at University of Edinburgh in Computer Science and Informatics?

FTE Category A staff submitted: 94.85

Research output data provided by the Research Excellence Framework (REF)

Click here to see the results for all UK universities

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