PhD Studentship in Privacy preserving machine learning for IoT data at University of Edinburgh on FindAPhD.com

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Dr R Sarkar No more applications being accepted Funded PhD Project (UK Students Only)

About the Project

A fully funded PhD position is available in the area of “Privacy preserving machine learning for IoT data”. The position is funded by GCHQ through the National Cyber Security Centre. Begins september 2018.

Topic description:
Large scale analysis of IoT data can help to optimise our systems — from home appliances to factories and infrastructure. However, they also pose a major privacy risk. Simple outputs of statistical analysis and machine learning can leak private information.

This project is about protecting the privacy of individuals without losing the benefits of large scale data analysis. We will combine fundamental aspects of privacy, optimisation and distributed computation to design algorithms that perform machine learning, but guarantee not to violate privacy.

Students should have interest in foundations of some of these areas: data science, optimisation, machine learning, distributed computation, algorithms etc.

Contact for application and queries:
Dr. Rik Sarkar.
email: [Email Address Removed]
http://homepages.inf.ed.ac.uk/rsarkar/

Funding Notes

Eligibility:
Applicants for the NCSC PhD position should have:

* BSc or equivalent qualification (with or without Masters) and

* UK citizenship

Students without UK citizenship, but still interested in the area can also apply for PhD in this topic, and are invited to get touch.

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Where will I study?

University of Edinburgh

One of the world''s top universities, consistently ranked in the world top 50 and placed 20th in the QS World University Rankings 2020. We provide a stimulating working, learning and teaching environment with access to excellent facilities and attract the world''s best, from Nobel Prize winning laureates to future explorers, pioneers and inventors.

PhD Studentship in Privacy preserving machine learning for IoT data

University of Edinburgh School of Informatics