NeuroAI: From machine learning to neurocomputational modelling of decision-making and learning

Summary

Decision-making and learning, often occurring in the face of uncertain information, are core components of cognition in humans and other organisms. The neurosciences and cognitive sciences of decision-making and learning have acquired large and complex data, which require advanced data science and artificial intelligence (AI) methods to elucidate their neural correlates. Neurobiologically plausible computational models and theoretical analysis can provide further insights into their underlying neural mechanisms and computational principles.

This Ph.D. research project will focus on two aspects: (i) developing and applying advanced AI and machine learning methods on neural and behavioural data; and (ii) developing biological neural network modelling. The data for analysis and modelling will be based on openly available data, and data from our research centre and collaborators’ labs.

This project is available in the Computer Science Research Institute and is tenable in the Faculty of Computing, Engineering and the Built Environment, at the Magee Campus.

The successful Ph.D. candidate will benefit from the expertise of Ulster University’s Cognitive and Computational Neuroscience, Neurotechnology, AI, Machine Learning and Computational Biology communities, and will interact closely with various leading international collaborators. The student will gain valuable knowledge in AI and machine learning techniques, computational modelling, high-performance computing, applications of mathematics/statistics, and the brain sciences. This training will provide wide opportunities for finding skilled work in academia or industry, especially in the burgeoning field of AI, data science/analytics and neuroscience.

In 2021, Ulster University was ranked 2nd in the UK for Ph.D. researcher satisfaction, 6th largest Computer Science and Informatics unit, and 7th for the level of world-leading or internationally excellent research and impact with respect to staff number.

Essential criteria

Applicants should hold, or expect to obtain, a First or Upper Second Class Honours Degree in a subject relevant to the proposed area of study.

We may also consider applications from those who hold equivalent qualifications, for example, a Lower Second Class Honours Degree plus a Master’s Degree with Distinction.

In exceptional circumstances, the University may consider a portfolio of evidence from applicants who have appropriate professional experience which is equivalent to the learning outcomes of an Honours degree in lieu of academic qualifications.

• Experience using research methods or other approaches relevant to the subject domain
• A demonstrable interest in the research area associated with the studentship

Desirable Criteria

If the University receives a large number of applicants for the project, the following desirable criteria may be applied to shortlist applicants for interview.

• First Class Honours (1st) Degree
• Masters at 70%
• For VCRS Awards, Masters at 75%
• Experience using research methods or other approaches relevant to the subject domain
• Work experience relevant to the proposed project
• Publications - peer-reviewed
• Experience of presentation of research findings

Equal Opportunities

The University is an equal opportunities employer and welcomes applicants from all sections of the community, particularly from those with disabilities.

Appointment will be made on merit.

Funding and eligibility

This project is funded by:

• Department for the Economy (DfE)
• Vice Chancellor's Research Scholarship (VCRS)

Our fully funded PhD scholarships will cover tuition fees and provide a maintenance allowance of £19,237 (tbc) per annum for three years* (subject to satisfactory academic performance).  A Research Training Support Grant (RTSG) of £900 per annum is also available.

These scholarships, funded via the Department for the Economy (DfE) and the Vice Chancellor’s Research Scholarships (VCRS), are open to applicants worldwide, regardless of residency or domicile.

Applicants who already hold a doctoral degree or who have been registered on a programme of research leading to the award of a doctoral degree on a full-time basis for more than one year (or part-time equivalent) are NOT eligible to apply for an award.

*Part time PhD scholarships may be available, based on 0.5 of the full time rate, and will require a six year registration period (individual project advertisements will note where part time options apply).

Due consideration should be given to financing your studies.