Funded PhD in Computer Science - 4 Years, UK/International

Northeastern University London; Greater London; On-site; GBP 18,000 - 20,000; Full time

Job summary

Northeastern University London invites applications for a funded PhD Studentship in collaboration with IMEC. The four-year program covers tuition fees, UKRI stipend, and London allowance, with start January 2027.

The project develops Bayesian and Ising models for MRAM devices, linking device statistics to probabilistic algorithms, using simulation and profiling tools to assess energy, latency and throughput across workloads such as TinyML and edge vision.

Qualifications

• Bachelor’s degree in a relevant subject with 2:1 or first-class honour (essential)
• Master’s degree in a relevant subject (optional)
• IELTS 6.5+ or equivalent if applicable (language requirement)

Responsibilities

• Develop robust methodologies for characterising the stochastic behaviour of MRAM devices.
• Establish links between device-level statistics and probabilistic algorithms.
• Build theoretical grounding in Bayesian and Ising models and how they can be optimized for MRAM characteristics.
• Use simulation and profiling frameworks to evaluate energy, latency and throughput.
• Benchmark across workloads such as TinyML, edge vision and federated learning.

Skills

Self-motivation

Good communication

Problem solving

Education

Bachelor's degree in Computer Science (2:1 or 1st)

Master’s degree (optional)

Tools

Bayesian modelling

MRAM hardware concepts

Job description

Northeastern University London invites applications for a funded PhD Studentship in collaboration with IMEC. The four-year program covers tuition fees, UKRI stipend, and London allowance, with start January 2027.

The project develops Bayesian and Ising models for MRAM devices, linking device statistics to probabilistic algorithms, using simulation and profiling tools to assess energy, latency and throughput across workloads such as TinyML and edge vision.