Northeastern University PhD Scholarship in Computer Science - Quantum Statistics

Northeastern University London Fully Funded PhD Scholarship in Computer Science Reliable Quantum Statistics

Northeastern University London >
Computing, Mathematics, Engineering & Natural Sciences

Funded PhD Project (UK or International Students)

Funding provider:
Northeastern University London (NU London)

Subject areas:

Project start date:
October 2026

Supervisors (
* lead):

• Osvaldo Simeone (Northeastern University London)
• Carlos Perez Delgado (University of Kent)

Aligned programme of study:
PhD in Computer Science

Mode of study:
Full-time

As part of a major investment, Northeastern University London (NU London) has multiple, fully-funded PhD studentships available to accelerate its interdisciplinary research in the humanities, social sciences and digital sciences. Each scholarship is fully-funded for three and a half years (UKRI rates) and includes fees, an annual stipend, an additional London allowance and associated costs, such as training.

NU London is both a UK university governed by UK higher education regulations, and the European campus of Northeastern University - a large, top-tier research intensive, Boston-based institution. Founded in 1898, Northeastern received $230.7m of external research funding in 2022, and is the recognized leader in experience-driven lifelong learning. It has campuses across the United States and Canada (in Boston;
Charlotte, North Carolina;
Portland, Maine;
Oakland, California;
San Francisco;
Seattle;
Silicon Valley; Arlington, Virginia; the Massachusetts communities of Burlington and Nahant; Toronto and Vancouver). Whilst the PhD will be a UK qualification, students will have the opportunity to engage with and visit the Northeastern University network overseas as part of their London-based doctoral studies, providing a truly unique and highly sought-after dimension to their research training.

The project aims to develop reliable, adaptive, and universal statistical methods a broad range of statistical inference tasks in quantum systems with applications to quantum sensing, computing and communications. Topics will include:

• Sequential and universal inference: adaptive measurement and stopping rules controlling type-I error with finite-sample guarantees.
• Quantum statistical modeling: use of quantum relative entropy, Fisher information, and variational quantum circuits for practical implementations.
• Causal and information-theoretic analysis: exploring relationships among quantum divergences and their role in statistical efficiency.
• Simulation and numerical validation: using small- to mid-scale quantum simulators and classical emulators to verify theoretical results.
• Applications: quantum sensing, computing, and communications.

• Have a proven, strong educational background in history or a related subject (see eligibility criteria)
• Be excited and inspired by the proposed project area
• Be a self starter
• Have good communication skills
• Have an inquiring mind and be willing to challenge themselves

The successful candidates will benefit from a brand new campus on the banks of the River Thames next to Tower Bridge. This is an interdisciplinary, vibrant research environment with international collaboration and networking opportunities and dedicated research space. It will form the hub of a highly experienced, multi-institution supervisory team from NU London and the University of Kent.

Shortlisted candidates will be interviewed in May 2026.

• Bachelor's degree in a relevant subject - 2:1 or 1st (essential)
• Master's degree in a relevant subject (optional)

If applicable – IELTS 6.5 overall (with a score of at least 6.5 in each individual component) or equivalent.

Applications are open to UK and international students. Please indicate if you are likely to require a visa on your application. We are unable to support visa costs.

This scholarship covers the full cost of tuition fees, an annual stipend and an additional London allowance (set at UKRI rates) for 3.5 years.

Participation in the equal opportunities section is encouraged, but voluntary.