Research Studentship in Neural Engineering

3.5-year D.Phil. studentship

Project: Sleep classification for implanted neurostimulation systems

Supervisors: Dr. Joram van Rheede, Prof. Timothy Denison

Deep brain stimulation (DBS) is a medical therapy for neurological disorders, in which an implanted system provides electrical impulses to dysfunctional brain areas to alleviate patients’ symptoms. Systems used in clinical practice normally provide the same stimulation all the time. State of the art systems now automatically adjust stimulation according to measured brain activity that is correlated with symptoms. However, our brain operates differently between sleeping and waking brain states, and an optimal system should take this into account.

The aim of this project is to develop brain state (sleep stage) classifiers based on the data available to implanted DBS systems, with the ultimate goal of enabling brain state optimised therapy. Specifically, this means developing sleep staging algorithms based on neural activity data (local field potentials, LFPs) from key deep brain stimulation targets including the basal ganglia and thalamus. Auxiliary data available to implanted devices include on-device accelerometers which may provide data on patient posture and behaviour. A first aim will be to establish the best possible sleep classification performance based on these data, but to enable sleep staging on implanted devices a key second aim is to explore classification approaches that are suitable for implementation on current and near-future DBS implants – low on processing and memory demands and low on power consumption.

You will work with previously collected intracranial EEG data from epilepsy patients, use accelerometry data from wearable devices, and work with Parkinson’s patients with deep brain stimulation implants at Manchester Metropolitan university to collect additional targeted accelerometry and LFP data for this project. Collaborators include Prof Andrew Sharott (Oxford), Prof. Nicola Ray (Manchester Metropolitan), and Prof. Mariska van Steensel (UMC Utrecht), and there will be opportunities for collaboration with industry partner Amber Therapeutics. 

Eligibility: This studentship is open to Home students (home fees plus stipend).

Award Value: Course fees are covered at the level set for Home students. The stipend (tax-free maintenance grant) is the UKRI Minimum Stipend.

Candidate Requirements:

Prospective candidates will be judged according to how well they meet the following criteria:

• A first class or strong upper second-class undergraduate honours degree in engineering, neuroscience, machine learning, or related fields

and/or merit/distinction-level performance in a relevant postgraduate degree (e.g. MSc) 

• Experience of working in a neuroscience, clinical or engineering research environment
• Proven ability to use a scientific programming language such as python or MATLAB for signal processing
• A desire to improve therapies available to patients with neurological conditions
• Excellent written and spoken scientific communication skills

The following skills are desirable but not essential: 

• Experience working with human participants and/or patients
• Experience in working with electrophysiological data
• Experience in sleep scoring
• Experience in classifier development
• Experience with signal processing on embedded / resource-constrained systems 

Application Procedure

Informal enquiries are encouraged and should be addressed to Dr Joram van Rheede, joram.vanrheede@bndu.ox.ac.uk

Candidates must submit a graduate application form and are expected to meet the graduate admissions criteria. Details are available on the course page of the University website.

Please quote 26ENGBIO_JVR in all correspondence and in your graduate application.

Application deadline: noon on 2 December 2025 (In line with the University admissions deadline set by the University)

Start date: October 2026