PhD Scholarship in Computer Science: Algorithms​/Hardware Co-Design Bayesian and Ising Models

About the Opportunity Northeastern University London Fully Funded PhD Scholarship in Computer Science Algorithms/Hardware Co-Design for Bayesian and Ising Models Northeastern University London >
Computing, Mathematics, Engineering & Natural Sciences Deadline: 15/11/2026 Funded PhD Project (UK or International Students) Funding provider:
Northeastern University London (NU London) and IMEC Subject areas:
Computer science, electronics Project start date:
January 2027 Supervisors (
* lead):

• Bipin Rajendran (Northeastern University London)
• Darren Hurley-Smith (University of Kent)

Aligned programme of study:
PhD in Computer Science Mode of study:
Full-time Northeastern University London As part of a major investment, Northeastern University London (NU London) offers PhD studentships to support interdisciplinary research across the humanities, social sciences and digital sciences. The current studentship is part-funded by IMEC and is offered for four years and includes funding towards fees, a stipend at UKRI rates, 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 The project aims to develop algorithms and hardware architectures for Bayesian and Ising Models that can leverage the intrinsic stochasticity of emerging magnetic random access memory (MRAM) devices. Topics will include:

• Develop robust methodologies for characterising the stochastic behaviour of existing MRAM devices.
• Establish the link between device‑level statistics and probabilistic algorithms.
• Build theoretical grounding in probabilistic models (Bayesian and Ising) and how they can be optimized considering the natural characteristics of MRAM devices.
• Use simulation and emulation tools combined with profiling frameworks for energy, latency, and throughput.
• Benchmark across representative workloads (e.g., TinyML, edge vision, federated learning).

The successful candidates will:

• 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 November 2026.

Candidates are welcome to contact the NU London supervisor with informal enquiries before the Final date to receive applications: 15/11/2026 () The panel will be shortlisting for this position on a rolling basis so please apply as soon as…