The School of Mathematics, Computer Science and Engineering at City, University of London is offering a three-year doctoral studentship for 2021/22 entry. The scholarship is one of two co-funded by Equideum Health
, a company working at the interface between blockchain, machine learning and privacy enhancing technologies to develop new healthcare solutions. The successful candidate will be supported by the Department of Computer Science and its academic staff (with extensive expertise in machine learning in healthcare) as well as deal with real-world challenges relative to industrial deployment.
Applications are invited from exceptional UK, European and International graduates wishing to pursue cutting-edge research in AI and healthcare, one of the School's key research areas. The School is investing in academic excellence following its success in the last REF, which highlighted the world class quality of its research.
Closing date: March 21st 2022
When querying an API or delegating the execution of an application to a third-party server, we are trusting the remote machine to execute the application or request correctly, and not return a "cheaper" result obtained by running a degraded version of the application that would consume less resources.
While this is generally not an issue when interacting with widespread public cloud operators who have their reputation at stake, the emergence of decentralised cloud platforms (iExec, Golem, ...) changes this assumption. In a decentralised cloud, the cloud operator does not run the infrastructure but instead aggregates compute resources from a large number of more or less reliable sources. This suggests a need to verify the correct execution of applications delegated to decentralised environments.
Zero-Knowledge proofs are becoming increasingly popular for their ability to help blockchains scale up and bring privacy to their transactions (Z-Cash, AZTEC, ...). Any kind of computation can be verified using ZKPs as long as one can express them in a suitable form. They remain however computationally demanding.
The goal of his PhD project is to develop various approaches including ZKPs to verify the computation of modern machine learning algorithms. Our primary application use-case will target models used for predictions in healthcare, including signal and image analyses tasks for classification and pattern recognition. The project will focus initially on verifying integrity for inference-time computations but potentially also develop methods for training algorithms. Execution integrity can open the doors to multiple improvements to the provider-payers interactions in the health insurance domain for instance.
What is offered
A doctoral studentship will provide:
An annual bursary (£16,000) with a substantial top-up salary offered by the company to outstanding candidates, for a total amount aligned to typical RA salaries in the UK.
Full tuition fee for Home students. Applications from international applicants are welcome but the applicant must make appropriate arrangements to cover the difference between the international and home tuition fee.
A budget for travel expenses and consumables (£4,000 in total).
The studentships will be awarded on the basis of outstanding academic achievement and the potential to produce cutting edge-research. Prospective applicants must:
Hold a good honours degree (normally no less than a second class honours degree or an equivalent qualification) in an appropriate subject. Exceptionally, if the first degree is in a different subject area, we can consider applications from those with a good Master’s Degree in a relevant subject or extensive professional experience in the area of their proposed research;
Be able to demonstrate proficiency in the use of oral and written English;
Applicants whose mother tongue is not English must meet any one or a combination of the following:
- A minimum IELTS average score of 6.5; with a minimum of 6.0 in each of the four components
- The award of a Masters’ degree, the teaching of which was in English from an English Speaking country.
How to Apply
Applicants are welcome to discuss their application in advance with the academic supervisor in the School Dr Giacomo Tarroni
If you wish to apply, you can do it here