At a Glance
- Tasks: Research post-quantum cryptography and develop trustworthy AI systems.
- Company: University of Sheffield, a leader in computer science and technology.
- Benefits: Fully funded PhD with a tax-free stipend of £25,000 per year.
- Other info: Collaborate with Defence Science and Technology Laboratory on innovative projects.
- Why this job: Join the forefront of AI and cryptography to tackle urgent global challenges.
- Qualifications: First-class degree in Computer Science or related field; strong maths and programming skills required.
The predicted salary is between 25000 - 25000 £ per year.
Are you ready to help shape the cryptographic foundations of the next generation of trustworthy, quantum-resilient AI systems?
The School of Computer Science at the University of Sheffield is inviting applications for a fully funded Ph D studentship offered in collaboration with the Defence Science and Technology Laboratory (DSTL), at the intersection of post-quantum cryptography , zero-knowledge proofs (ZKPs) , and trustworthy AI .
This is a rare opportunity to work on a problem that sits right at the frontier of two of the most urgent challenges in modern computing: the looming threat quantum computers pose to current cryptographic infrastructure, and the growing need for AI systems whose outputs can be verified, audited, and trusted without exposing sensitive data or models.
This opportunity is primarily intended for candidates who qualify for UK home student rates.
The studentship includes a competitive, tax-free stipend of approximately £25,000 per year , which exceeds the standard UKRI rates, and is subject to annual inflationary adjustments.
Research themes include: Designing efficient, lattice- or code-based zero-knowledge proof systems resilient to quantum attacks Verifiable and privacy-preserving machine learning (e. g. proving model integrity or fairness without revealing training data) Scalable ZK-proof constructions for federated and decentralised AI pipelines Formal security analysis of post-quantum ZKP protocols in real-world AI deployments School of Computer Science at the University of Sheffield.
A leading centre for security, machine learning, robotics, and autonomous systems.
The student will join a research group working at the interface of advances in machine learning, security and post-quantum cryptography, with opportunities to collaborate with partners in robotics, autonomous systems and AI safety.
Access to modern computing facilities and experimental platforms (e. g. robotic testbeds or simulators) will be available depending on the final focus of the work.
Defence Science and Technology Laboratory (Dstl).
As the Ministry of Defence (MOD)’s in-government science and technology organisation, Dstl provides unique expertise, insight and innovation to maintain UK warfighting readiness in an increasingly dangerous and complex world.
As MOD's science and technology leaders, Dstl provides expert advice, analysis, and capability across a wide range of applications, including robotics and autonomous systems, AI, and Data Science.
Eligibility and Desired Background Applicants should hold (or expect to obtain) a first‑class or strong upper‑second‑class degree, or a Master’s degree, in a relevant discipline such as Computer Science, Applied Mathematics or a closely related field.
A strong mathematical background and proficiency in programming (preferably Python) are essential.
Prior exposure to one or more of the following: machine learning, information security, modern crypto systems will be an advantage.
The Ph D studentship will cover standard UK home tuition fees and provide a tax-free stipend of £25,000 for 3.5 years. #J-18808-Ljbffr
PhD Studentship: Post-Quantum Zero-Knowledge Proofs and Trustworthy AI employer: University of Sheffield
The University of Sheffield offers an exceptional environment for PhD candidates, particularly in the School of Electrical and Electronic Engineering, where cutting-edge research in machine learning and autonomous systems thrives. With a fully funded studentship that includes a generous tax-free stipend, students benefit from access to modern facilities and collaborative opportunities with leading experts at the Defence Science and Technology Laboratory. The supportive work culture fosters innovation and personal growth, making it an ideal place for aspiring researchers to develop their skills and contribute to impactful projects.
StudySmarter Expert Advice🤫
We think this is how you could land PhD Studentship: Post-Quantum Zero-Knowledge Proofs and Trustworthy AI
✨Join Data-Science Meetups
Get yourself along to local data-science meetups or workshops. They're goldmines for networking, and you'll learn from industry pros who might just point you in the direction of internships. Plus, discussing the latest trends with like-minded individuals can really amp up your game.
✨Utilise University Career Services
Check in with your uni's career services since they often have connections with companies looking for interns. They might even organise information sessions with firms, which can be a great chance for you to learn more about potential internships and make some key contacts.
✨Show Off Your Stuff on GitHub
If you're into data science, having a GitHub profile with your projects is essential. Make sure your portfolio is public and showcases your best work! Recruiters love to see your coding skills and problem-solving approach, and it’s a brilliant way to stand out.
✨Apply Directly on Our Website
Don’t forget to check out the internships listed on our site! It's always a good idea to apply directly through our website because it makes your application easier for our team to find, and you might just catch the hiring manager’s eye by showcasing exactly what you're passionate about in data science.
We think you need these skills to ace PhD Studentship: Post-Quantum Zero-Knowledge Proofs and Trustworthy AI
Some tips for your application 🫡
Show Off Your Technical Skills:For a data science internship, we want to see those analytical skills shine! List your programming languages, like Python or R, and make sure to highlight any relevant projects or courses you've completed. If you've dabbled with tools like Pandas, NumPy, or machine learning algorithms, don’t hold back – include those in your CV!
Share Your Curiosity in Your Cover Letter:As an intern, your motivation and eagerness to learn are key! In your cover letter, talk about specific data science concepts that excite you and how this internship at University of Sheffield will help you grow. Share what you hope to achieve and how you plan to tackle real-world data problems - we love enthusiasm!
Include Any Relevant Certifications:If you've earned any certifications, such as from Coursera or DataCamp, make sure to include these in your application. They show us that you're proactive and committed to expanding your data science skillset. This could make a real difference in how we assess your application!
Keep It Relevant and Concise:Remember, as an intern, you don’t need to have decades of experience. Focus on showcasing relevant coursework, personal projects, or even related volunteer work in data science. Keep your CV and cover letter concise but impactful – we appreciate clear and straightforward communication!
How to prepare for a job interview at University of Sheffield
✨Brush Up on Your Coding Skills
As a data science intern, you might get grilled on your programming skills. Expect to tackle some coding challenges using languages like Python or R. We recommend practising basic algorithms or data manipulation tasks so you can show off your tech skills with confidence.
✨Show Off Your Projects
Prepare to discuss any projects you’ve done, whether in your studies or on your own time. Having a strong portfolio of data analyses or machine learning models will really set you apart. We can use platforms like GitHub to showcase your work to impress University of Sheffield.
✨Know Your Stats and ML Basics
Brush up on your statistics and machine learning concepts because interviewers love to dig into this! Be ready to explain your understanding of algorithms or how you would approach a given data problem. This will highlight your theoretical background alongside your practical skills.
✨Be Eager to Learn and Adapt
Internships are all about potential and growth. Make sure you convey your eagerness to learn and adapt to new tools or methodologies. Show University of Sheffield that you’re not just looking for experience, but that you're keen to contribute and grow within the team.
