Fighter pilots experience high cognitive loads (termed “cognitive overload”) because of complex, multimodal and time sensitive information environments. The complexity and multimodal aspect are due to the vast amount of potentially critical information that different instruments and sensors provide in various modalities. The time sensitive aspect is due to fact that a delay in observing, comprehending and in turn, reacting to critical information could be fatal. This means that pilots have to utilise and engage with the right instrument and sensor at the right time and use that information to make the best possible decision all within a very short space of time.
The overall goal of this research is to make a fundamental first step in establishing that pilots’ cognitive overload can be detected based on a series of brain activations and reacted upon them by cockpit information systems. Early research in neuropsychology has indicated that it is possible to monitoring cognitive load. However, this research is still in its infancy. This project will push the boundaries of science by establishing that cognitive overload can be detected based on a series of brain activations. We also aim to go one step further and detect the modality of cognitive overload, i.e. either it is visual, auditory or kinaesthetic, in real-time, from the brain signals. Finally, we aim to investigate if the brain activates that have been identified are common across users, or they are unique to each individual.
Therefore, during the project, Electroencephalography (EEG) monitoring and modelling techniques will be employed to capture brain signals when participants are experiencing cognitive overload. Artificial Intelligence models will then be devised to learn and detect from the brain signals whether a user is experiencing a cognitive overload and what modality of cognitive overload would that be at a given time.
This PhD will entail undertaking cutting edge research into new and novel technologies, developing Human Machine Interfaces where the research outcomes could be tested and deployed in practical applications. This project has BAE Systems as an external sponsor.
- Applicants should have, or expect to achieve, at least a 2:1 Honours degree (or equivalent) or Master’s degree in a relevant subject, e.g. Computing Science, Artificial Intelligence, Data Science, Neuroscience, Neuroergonomics, etc.
- Excellent written and oral English language skills (acquiring the minimum test scores if English is not your first language).
- Excellent communication skills (verbal and written).
- Understanding of the research lifecycle (ability to state hypotheses, design new methods, implement prototypes, evaluate methods and interpret results, adapt methods). Prior experience of data analysis and machine learning.
- Prior knowledge of deep learning and/or transformer models.
- Prior experience of EEG data analysis including pre-processing, and/or modelling.
- Experience in conducting EEG experiments and user assessments.
- Excellent analytical skills and a demonstrable aptitude to undertake research and develop into an independent researcher.
- Ability to work with external partners and collaboratively.
- Ability to work pro-actively and able to think creatively, having the courage to challenge and drive improvement.
All home and international students are eligible to apply which will cover the full stipend and tuition fees at the home rate (not the international rate). It includes:
- A fee waiver equivalent to the Home rate; and
- A tax-free stipend of approx. £15,609 p.a. for a maximum of four years and does not need to be paid back. This amount will increase every year, typically with inflation.
To be classed as a home student, applicants must meet the following criteria:
- Be a UK national (meeting residency requirements), or
- Have settled status, or
- Have pre-settled status (meeting residency requirements), or
- Have indefinite leave to remain or enter.
The residency requirements are based on the Education (Fees and Awards) (England) Regulations 2007 and subsequent amendments. Normally to be eligible for a full award a student must have no restrictions on how long they can stay in the UK and have been ordinarily resident in the UK for at least 3 years prior to the start of the studentship (with some further constraint regarding residence for education). If a student does not meet the criteria above, they will be classed as an international student. The international portion of the tuition fee cannot be funded by the UKRI grant and must be covered from other sources. International students are permitted to self-fund the difference between the home and international fee rates. We also welcome self-funded or externally funded applications.
Additional support for your doctoral studies
- The studentship offers access to training, networking and development opportunities to help you build a research and innovation career.
- As a UKRI-funded doctoral student, you will be able to access additional funding to cover the cost of other related training and development opportunities including conference attendance, internships or placements with the industry partner.
How to apply
Apply by sending an email to Dr Yashar Moshfeghi ([Email Address Removed]) with the title “UKRI PhD Studentship – Cognitive Overload Detection” and the following documents as attachments:
A covering letter (max four pages) which includes:
- your full contact details
- If you would like to be considered for the funding or if you have already funding in place (self-funding or external funding),
- Your motivation to apply for this position, including how we can add value to your proposed research and how you can bring value to us along with your future career aspirations
- How your background and previous experience meet the requirements detailed above, and
- A detailed description of your understanding of the topic including a short literature review as well as a particular research question you want to pursue on this topic (minimum two pages).
Also send on please:
- a copy of an up-to-date CV.
- transcripts and certificates of all degrees
- proof of English language proficiency, less than two years old, if English isn't your first language
- Two references, one of which must be academic
Contact Dr Yashar Moshfeghi ([Email Address Removed]) to discuss your interest in applying for the position by the 8th of June, 2022. Applicants will be interviewed as soon as possible after they formally apply.