Overview. The Computational Privacy Group, led by Dr. Yves-Alexandre de Montjoye, at Imperial College London’s Data Science Institute at the Department of Computing has funded openings for PhD students (from UK, EU and overseas) to work on topics related to privacy, data protection, and the impact of algorithms on society.
Topics of current interests include, for instance, individual privacy in large-scale behavioral datasets; re-identification attacks against privacy-preserving data systems or aggregates, privacy of machine learning models, privacy engineering solutions such as differential privacy and query-based systems, ethics and fairness in AI, and computational social science.
Research context. For the first time in history, we have the ability to amass large amounts of medical, behavioral and social demographic data about humans and societies. While this data has the potential to fundamentally transform industries such as healthcare and transportation, its collection and use also pose significant challenges. The data itself can be prone to serious privacy violations, while the algorithm-based solutions built on top of it may open the way to large-scale discrimination and bias.
Research projects. Projects are defined in close collaboration with the student, but could tackle, for example:
- The definition of formal properties and metrics of privacy or fairness in AI decision-making;
- The development of privacy-enhancing data processing systems;
- The development of new machine learning techniques for behavioral user fingerprinting.
Our projects include a mix of theoretical and empirical work with large-scale data from mobile phones, credit card transactions, or browsers, possibly in collaboration with industry partners.
All our projects aim to generate significant societal impact. We want to answer novel and relevant research questions, with the potential to change how people, policymakers, and industry leaders think about privacy and the impact of AI. Our research has been published in top journals such as Nature Communications and Science and top CS conferences and has been widely cited in the press and public policy documents.
We are looking for candidates who love exploring ideas to discover and create new things, are willing to collaborate with others, and would like to generate impact through their research.
Diversity. We believe in the importance of diversity in both our group and the research fields we work in. We aim to create and foster a collaborative environment within the group where everyone feels welcome. We encourage applicants of all backgrounds and ages to apply, in particular women, disabled, BAME and LGBTQIA+ candidates. Imperial College London is committed to equality, diversity and inclusion.
Recommended prerequisites. MSc or MEng (4y BEng will be considered) in computer science, statistics, mathematics, physics, electrical engineering, or a related field. Experience in data science, statistics and/or machine learning is a plus.
About Imperial. Imperial College London, ranked 9th globally, is one of the top universities in the world. A full-time PhD at the South Kensington Campus takes 3-4 years, is fully funded and usually starts in October or January. Regarding Brexit, Imperial takes a proactive approach, fostering research collaboration globally and within Europe. Imperial President Alice Gast has made very clear that “Imperial is, and will remain, a European university” and will ensure that legislative changes to students’ right to work and freedom of movement will not impact their academic aspirations.
Logistics. Imperial uses a centralised application system on which the full application (CV, research statement, transcripts, and names for 2 recommendation letters) needs to be submitted by the deadline (please select Dr. Yves-Alexandre de Montjoye as the “Proposed research supervisor”, Computing PGR as degree, and G5ZP as course code.).
Interested candidates are, however, strongly encouraged to independently: