Computational modelling of decision uncertainty awareness and learning: From Computational Neuroscience of metacognition to AI applications

Computing, Engineering and the Built Environment         ·        Londonderry, United Kingdom        ·       Full time

Summary

It is well known that some animals, particularly humans, have a sense of self-awareness. Awareness can be reported or inferred when undergoing various forms of cognitive tasks such as when making decisions. Highly studied tasks in which such metacognition is present include perceptual decision-making, which involves the transformation of sensory perception into a single decision, typically requiring some form of evidence accumulation over time [1]. Our previous computational modelling work has developed a biologically based neural network model for monitoring decision uncertainty level on-the-fly [2]. Our model could replicate certain key characteristics of decision uncertainty (or its reciprocal, decision confidence), while also accounting for change-of-mind behaviour via internal feedback control mechanism [2, 3].

This Ph.D. project aims to use computational modelling and mathematical analysis to further understand the computational principles underlying decision uncertainty awareness. Model’s behaviours will be compared to experimental data (e.g. [4]), including data from collaborator labs and open data. Computational models will be extended for machine self-awareness and novel brain-inspired learning algorithms for AI applications. This timely and exciting 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 PhD candidate will benefit from the expertise of Ulster University’s Computational Neuroscience, Cognitive Neuroscience, AI, Machine Learning and Computational Biology communities, and will interact closely with various leading international collaborators. The student will gain valuable knowledge in data mining and machine learning techniques, computational modelling, high-performance computing, applications of mathematics/statistics, and the brain sciences. These are essential in many areas of science, engineering, mathematics, and health and biomedical sciences. This training will provide wide opportunities for finding skilled work, especially in the burgeoning field of AI and data science/analytics

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 comprehensive and articulate personal statement

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

Funding and eligibility

The University offers the following levels of support:

Vice Chancellors Research Studentship (VCRS)

Full award (full-time PhD fees + DfE level of maintenance grant + RTSG for 3 years).

This scholarship will cover full-time PhD tuition fees and provide the recipient with £18,000 (tbc) maintenance grant per annum for three years (subject to satisfactory academic performance).

This scholarship also comes with £900 per annum for three years as a research training support grant (RTSG) allocation to help support the PhD researcher.

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.

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.

Vice-Chancellor’s Research Bursary (VCRB)

Part award (full-time PhD fees + 50% DfE level of maintenance grant + RTSG for 3 years).

This scholarship will cover full-time PhD tuition fees and provide the recipient with £8,000 maintenance grant per annum for three years (subject to satisfactory academic performance). This scholarship also comes with £900 per annum for three years as a research training support grant (RTSG) allocation to help support the PhD researcher.

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.

Vice-Chancellor’s Research Fees Bursary (VCRFB)

Fees only award (PhD fees + RTSG for 3 years).

This scholarship will cover full-time PhD tuition fees for three years (subject to satisfactory academic performance). This scholarship also comes with £900 per annum for three years as a research training support grant (RTSG) allocation to help support the PhD researcher.

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.

Department for the Economy (DFE)

The scholarship will cover tuition fees at the Home rate and a maintenance allowance of £18,000 (tbc) per annum for three years (subject to satisfactory academic performance).

This scholarship also comes with £900 per annum for three years as a research training support grant (RTSG) allocation to help support the PhD researcher.

• Candidates with pre-settled or settled status under the EU Settlement Scheme, who also satisfy a three year residency requirement in the UK prior to the start of the course for which a Studentship is held MAY receive a Studentship covering fees and maintenance.
• Republic of Ireland (ROI) nationals who satisfy three years’ residency in the UK prior to the start of the course MAY receive a Studentship covering fees and maintenance (ROI nationals don’t need to have pre-settled or settled status under the EU Settlement Scheme to qualify).
• Other non-ROI EU applicants are ‘International’ are not eligible for this source of funding.
• 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.

Due consideration should be given to financing your studies. Further information on cost of living

Recommended reading

[1] O’Connell, Shadlen, Wong-Lin and Kelly (2018) Bridging neural and computational viewpoints on perceptual decision-making. Trends in Neurosciences, 41(11):838-852.

[2] Atiya, Rano, Prasad and Wong-Lin (2019) A neural circuit model of decision uncertainty and change-of-mind. Nature Communications, 10(1):2287. doi: 10.1038/s41467-019-10316-8.

[3] Atiya, Zgonnikov, O’Hora, Schoemann, Scherbaum and Wong-Lin (2020) Changes-of-mind in the absence of new post-decision evidence. PLoS Computational Biology, 16(2):e1007149. doi:10.1371/journal.pcbi.1007149.

[4] Fernandez-Vargas, Tremmel, Valeriani, Bhattacharyya, Cinel, Citi and Poli (2020) Subject- and task-independent neural correlates and prediction of decision confidence in perceptual decision making. Journal of Neural Engineering, 18(2021): 046055.

The Doctoral College at Ulster University

Please click here to apply.