DPhil Studentship: How Brain Network Dynamics Shape Human Cognition

University of Oxford; Oxford; In loco; GBP 20.000 - 25.000; Tempo pieno

Vantaggi offerti da questo lavoro

UKRI stipend

Fees covered

Descrizione del lavoro

University of Oxford invites applications for a fully funded DPhil in Cognitive Neuroscience within the Department of Psychiatry. The project investigates how brain network dynamics shape human cognition using MEG, computational modelling and cognitive experiments.

You will join Dr Mats van Es' group at OHBA, contributing to MEG analyses, experimental design, and machine-learning based investigations while developing research questions and communicating findings.

Competenze

• A relevant Master’s degree or equivalent in neuroscience, psychology, physics, engineering or computer science.
• Strong quantitative and computational skills are essential.
• Experience with electrophysiology methods (MEG/EEG) is advantageous.

Mansioni

• Analyse large MEG datasets to characterise network dynamics over time.
• Design and conduct MEG experiments to test hypotheses about brain timing and cognition.
• Develop computational models or closed-loop experiments to test how network timing influences behavior.
• Collaborate in an interdisciplinary environment and communicate findings.

Conoscenze

Python

Statistical modelling

Machine learning

Experimental design

Formazione

Upper second-class honours degree (or equivalent)

Master's degree in cognitive neuroscience or related fields

Strumenti

MEG

EEG

MRI

Descrizione del lavoro

How Brain Network Dynamics Shape Human Cognition

DPhil in Cognitive Neuroscience, Department of Psychiatry, University of Oxford | October 2027

This fully funded Department of Psychiatry project investigates how the timing and coordination of brain network activity shape human cognition. Combining magnetoencephalography (MEG), computational modelling and cognitive experiments, it aims to uncover the neural dynamics underlying flexible behaviour.

The Group

You will join Dr Mats van Es' research group at the Oxford Centre for Human Brain Activity (OHBA), part of the Oxford Centre for Integrative Neuroimaging (OxCIN). Building on our recent discovery of recurring cycles of brain network activity, we develop computational approaches to understand their underlying mechanisms, functional significance and potential for intervention.

The DPhil

The project, refined with the successful candidate, will investigate how brain network dynamics vary across cognitive contexts and whether their temporal organisation constrains behavioural performance.

You will analyse large MEG datasets to characterise how networks interact and transition over time, and test whether these dynamics predict reaction times and accuracy during memory, perception and decision-making tasks. You will also help design and conduct new MEG experiments to test hypotheses about the functional role of network timing.

Depending on your interests, the project may extend to computational modelling or closed-loop experiments, in which ongoing brain activity determines the timing of task events. These approaches offer opportunities to test whether manipulating network timing can influence cognition and behaviour.

Training/supervision

You will receive training in advanced MEG analysis, computational modelling of brain dynamics (including machine learning methods), experimental design and statistical inference. You will develop skills in formulating research questions, open-science and reproducible research, and communicating scientific findings.

You will benefit from close supervision, an interdisciplinary research environment and access to state-of-the-art MEG, MRI and neuromodulation facilities and high-performance computing. Opportunities for international collaboration and conference presentations will support your scientific independence and career development.

Candidate profile

We welcome applicants with at least an upper second-class honours degree (or equivalent) and/or a relevant Master's degree in cognitive neuroscience, psychology, neuroscience, physics, engineering, computer science or related fields.

We seek candidates with a strong interest in human cognition, excellent quantitative and computational skills (ideally Python), and experience with electrophysiology (MEG or EEG). Experience in experimental design, cognitive modelling or machine learning is advantageous. Independent research experience, scientific curiosity, and strong communication and collaboration skills are important. We are committed to equality, diversity, and inclusion and encourage applications from all backgrounds.

Funding/application

The scholarship covers course fees up to the value of home fees*, a tax-free stipend at the UKRI standard rate (no less than £22,460 per annum), plus additional support for research expenses and conference attendance.

*Applicants with overseas fee status would need to fund the fee difference from alternative sources.

For informal enquiries please contact: [e-mail]

Submission deadline: 12:00 noon UK time on Friday 27th November 2026 (NOTE: this is earlier than the University’s December deadline)

Interview date w/c 14th December 2026