Doctoral student in a lab

Digital Signal Processing of Electroencephalograph (EEG)

  • School: School of Science and Technology
  • Starting: 2019
  • Funding: UK student / EU student (non-UK) / International student (non-EU) / Fully-funded


The project will involve collaboration with King’s College and University College London in processing of EEG and jointly recorded EEG-fMRI data for detection, monitoring, prediction, and localisation of anomalies within the brain. It follows previous and current research works undertaken by the research team under Professor Saeid Sanei for various brain disorders and abnormalities such as seizure, dementia, stress, mental fatigue, sleep, and emotions.

During the course of this project, suitable signal processing and machine learning algorithms will be developed to model the brain function and recognise the state of anomaly in the brain function for a particular abnormality.

During the course of this project, the student will enhance her/his knowledge on new techniques in signal processing and machine learning such as adaptive cooperative networking, statistical optimisation, advances on deep neural networks and how to publish her/his research outcome in foremost scientific journals and prestigious conference proceedings. The outcome of this research will primarily benefit a large community of patients suffering from brain diseases and their siblings. It will also benefit academic community within Engineering, Computer Science, and Math who will use the developed techniques and algorithms.

The applicants are expected to have sufficient background in digital signal processing and machine learning and show enthusiasm in working together with other members of the research team. The selected candidate will collaborate with groups in Computer Science, Engineering, and Clinicians and gain sufficient knowledge to build up their future as an academic or technology scientist.


Professor Saeid Sanei

Entry qualifications

Entrants must have an MSc, in one of the following subjects: Electrical & Electronic Engineering, Communications, Biomedical Engineering, or Computer Science at Distinction or Merit graduated from a reputed UK or International University.

How to apply

How to apply

The deadline for applications is 12 pm (UK time) 07 January 2019.

Download an application form here.
Please make sure you take a look at our application guidance notes before making your application.

Further information on how to apply can be found on this page.

Fees and funding

This is a fully funded NTU studentship, covering UK/EU fees and paying a stipend in line with UKRI.

Applications from non-EU students are welcome, but a successful candidate would be responsible for paying the difference between non-EU and UK/EU fees.

Guidance and support

Further guidance and support on how to apply can be found on this page.

Still need help?

Saeid Sanei