Project Overview
About the Scholarship
This Surrey project develops federated machine unlearning: methods for removing the influence of selected data from distributed models. The aim is to make removal verifiable while protecting privacy and preserving useful model performance.
Research Areas
- Machine learning
- Privacy-preserving AI
- Computer science
Funding and Duration
| Component | Details |
|---|---|
| Award or position | PhD scholarship / studentship |
| Stipend / salary | GBP 21,805/year (2026/27 reference rate) |
| Tuition | Home-rate funding; international support requires confirmation |
Eligibility and Requirements
| Criterion | Requirement |
|---|---|
| Applicant eligibility | Programme and project criteria apply; see official eligibility guidance |
| Further conditions | Home-rate fees covered; international fee support must be confirmed. |
Application dates
| Component | Details |
|---|---|
| Recruitment status | Open |
| Deadline / consideration round | 31 October 2026 |
| Location | United Kingdom |
About University of Surrey
Surrey offers doctoral research in science, engineering, health and other fields. Its advertised studentships set out a defined research problem, supervision arrangements and the funding available for that project.
Official details: Read the programme or project information
Application route: Follow the official application instructions
Contact
Questions about this position, eligibility or the application process should be raised through the contact channel given on the official announcement page (see the Official Link section above). Always quote the position reference in your message so the admissions or HR team can route your enquiry quickly.
Official Link
Full announcement and application portal: https://www.surrey.ac.uk/fees-and-funding/studentships/robust-certified-and-scalable-federated-machine-unlearning-privacy-preserving-ai-0
Source: surrey.ac.uk - the details in this listing were recorded from this official page.
Important Notes
- Application deadline: 31 October 2026 - late or incomplete applications are normally not considered.
- Listing details were recorded from the official source at the time of publication; always confirm the latest requirements on the official page before applying.
- Prepare the documents listed in the eligibility and application sections before starting the online form - transcripts, CV and references take the longest to collect.
How to Apply
Submit your application through the official portal before the deadline: 31 October 2026. Read the eligibility requirements carefully and prepare all requested documents — early applications are strongly recommended for competitive awards.
Open the official application page ↗
Application guides
Frequently asked questions
Drawn from this listing's own record. Always confirm the details on the official source before applying.
What is the deadline for PhD Studentship in Federated Machine Unlearning for Privacy-Preserving AI, Surrey?
The application deadline is 31 October 2026. Applications received after that date are not considered, so treat it as a hard cut-off (Europe/London time) and leave time for references and transcripts. Closing time not specified — confirm with the provider before you leave it until the last day: the source names Europe/London but gives no clock time.
How is PhD Studentship in Federated Machine Unlearning for Privacy-Preserving AI, Surrey funded?
This is a partially funded award: funding is listed as partial, so it covers only part of the cost rather than the whole programme. What is covered (fees, living costs or both) is not set out in the source — check the source for what it covers and price the remainder before you apply. GBP 21,805/year (2026/27 reference rate).
Who is eligible to apply for PhD Studentship in Federated Machine Unlearning for Privacy-Preserving AI, Surrey?
This opportunity is open to applicants worldwide. Host-country status is not a requirement, although you must still satisfy the visa rules for United Kingdom. Applications are assessed by University of Surrey.
How do I apply for PhD Studentship in Federated Machine Unlearning for Privacy-Preserving AI, Surrey?
Applications for PhD Studentship in Federated Machine Unlearning for Privacy-Preserving AI, Surrey are submitted directly to University of Surrey through the provider's own application portal — use the Apply button on this page to open it. NextApply does not process applications or charge a fee.
Is an English proficiency test required for PhD Studentship in Federated Machine Unlearning for Privacy-Preserving AI, Surrey?
Yes — an English-language certificate is required for this listing. Check the exact band expected on the official source, since it can differ by programme. Requirements for United Kingdom are published by the provider.
What study level does PhD Studentship in Federated Machine Unlearning for Privacy-Preserving AI, Surrey offer?
This listing is offered at PhD level. That describes the qualification on offer, not a credential you must already hold — check the provider's stated entry requirements before applying.