PhD Study : Neural Data Science, Computational Neuromodulation, and Metalearning

Summary

The project is a collaboration between Ulster University and the University of Oxford (amongst other collaborators) on the computational modelling and theoretical development of neuromodulation in decision-making and learning [1-3]. Research in computational neuromodulation aims to develop and use computational models to understand how neuromodulators (endogeneous brain chemicals) influence brain functions and behaviour [1]. This includes the modulation of decision processing [2], and “learning to learn” i.e. metalearning [3].

The Ph.D. programme will involve the:

(i) use of machine learning techniques to analyse neural and behavioural data (neural data science) [4];

(ii) development of computational models across scales [5-9]; and

(iii) development of novel neuro/bio-inspired learning algorithms [3].

The project outputs will have implications not only on fundamental brain/cognitive sciences and artificial intelligent (AI) systems, but also on understanding brain disorders. This timely and exciting project is available in the Intelligent Systems Research Centre (ISRC) 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, AI, Machine Learning and Computational Biology communities, and will interact closely with the University of Oxford’s colleagues. 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 the health and biomedical sciences. This training will provide wide opportunities for finding skilled work, especially in the burgeoning field of data science and analytics.

References:

[1] Dayan, P. (2012) Twenty-five lessons from computational neuromodulation. Neuron, 76(1): 240-256.

[2] Doya, K. (2008) Modulators of decision making. Nature Neuroscience, 11(4): 410-416.

[3] Doya, K. (2002) Metalearning and neuromodulation. Neural Networks, 15(4-6): 495-506.

[4] Paninski, L., Cunningham, J.P. (2018) Neural data science: Accelerating the experiment-analysis-theory cycle in large-scale neuroscience. Current Opinions in Neurobiology, 50:232-241.

[5] Wong-Lin, K. Wang, D.H., Moustafa, A.A., Cohen, J.Y., Nakamura, K. (2017) Toward a multiscale modeling framework for understanding serotonergic function. Journal of Psychopharmacology, 31(9):1121-1136.

[6] Joshi, A., Youssofzadeh, V., Vemana, V., McGinnity, T.M., Prasad, G., Wong-Lin, K. (2017) An integrated modeling framework for neural circuits with multiple neuromodulators. The Journal of Royal Society Interface, 14(127). pii:20160902. doi: 10.1098/rsif.2016.0902.

[7] Flower, G., Wong-Lin, K. (2014) Reduced computational models of serotonin synthesis, release, and reuptake. IEEE Transactions on Biomedical Engineering, 61(4):1054-1061.

[8] Wang, D.H., Wong-Lin, K. (2013) Co-modulation of dopamine and serotonin on prefrontal cortical rhythyms: a theoretical study. Frontiers in Integrative Neuroscience, 7:54. doi: 10.3389/fnint.2013.000054.

[9] Wong-Lin, K., Joshi, A., Prasad, G., McGinnity, T.M. (2012) Network properties of a computational model of the dorsal raphe nucleus. Neural Networks, 32:15-25.

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.

• 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%
• Publications - peer-reviewed
• Experience of presentation of research findings
• Applicants will be shortlisted if they have an average of 75% or greater in a first (honours) degree (or a GPA of 8.75/10). For applicants with a first degree average in the range of 70% to 74% (GPA 3.3): If they are undertaking an Masters, then the average of their first degree marks and their Masters marks will be used for shortlisting.

Funding and eligibility

The University offers the following levels of support:

Vice Chancellors Research Studentship (VCRS)

The following scholarship options are available to applicants worldwide:

• Full Award: (full-time tuition fees + £19,000 (tbc))
• Part Award: (full-time tuition fees + £9,500)
• Fees Only Award: (full-time tuition fees)

These scholarships will cover full-time PhD tuition fees for three years (subject to satisfactory academic performance) and will provide a £900 per annum research training support grant (RTSG) 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.

Please note: you will automatically be entered into the competition for the Full Award, unless you state otherwise in your application.

Department for the Economy (DFE)

The scholarship will cover tuition fees at the Home rate and a maintenance allowance of £19,000 (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