Developing an AI-enabled point-of-care monitoring system to detect systemic concentration of therapeutics in blood

Apply and key information  

This project is funded by:

    • DFE-US-Ireland partnership programme


According to the World Health Organization, around 50 million people worldwide have epilepsy, making it one of the most common neurological diseases globally. Furthermore, it is estimated that up to 70% of patients with epilepsy (PWE) could live seizure-free if properly diagnosed and treated. There is a clear unmet clinical need for a point of care (POC) device capable of monitoring antiepileptic drugs (AEDs) levels in patients.

As part of a larger project funded by US-Ireland tripartite programme (USI-207), this PhD studentship will aim to develop an AI system from combined high dimensionality surface-enhanced Raman scattering (SERS) and electrochemical data sets to identify different concentration of AEDs in a patient’s blood while addressing data variability.

The AI system will be transparent (by knowing how the system reached a particular answer), justifiable (elucidating why the solution provided is acceptable), informative (providing new information to decision-makers), and reliable (using a quantifiable metric). To meet this goal, state-of-the-art explainable deep learning and evolutionary algorithms will be explored.

The successful PhD candidate will collaborate with researchers from Dublin City University (IR), Trinity College Dublin (IR) and Texas A&M University (US). The candidate will also benefit from the wide expertise of the university’s Computational Neuroscience and Machine Learning community and will gain valuable knowledge in machine learning, transfer learning, high-performance computing, mathematics/statistics and neuroscience and develop skills in commercialization of research outputs for licensing and patents.

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

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:

  • DFE-US-Ireland partnership programme

The scholarship will cover tuition fees at the Home rate and a maintenance allowance of £18,622 per annum for three years (subject to satisfactory academic performance).

*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 are eligible to 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.

Recommended reading

1.Krasowski, M. D. Therapeutic Drug Monitoring of the Newer Anti-Epilepsy Medications. Pharmaceuticals. 2010. 2.Jacob, S.; Nair, A. B. An Updated Overview on Therapeutic Drug Monitoring of Recent Antiepileptic Drugs. Drugs R. D. 2016, 16 (4), 303–316. 3.Murdoch, W. J.; Singh, C.; Kumbier, K.; Abbasi-Asl, R.; Yu, B. Definitions, Methods, and Applications in Interpretable Machine Learning. Proc. Natl. Acad. Sci. U. S. A. 2019. 4.Chander, A.; Srinivasan, R. Machine Learning and Knowledge Extraction; 2018. 5.Miguel Antonio, L.; Coello Coello, C. A. Coevolutionary Multiobjective Evolutionary Algorithms: Survey of the State-of-the-Art. IEEE Trans. Evol. Comput. 2018. 6.Cooney, C.; Folli, R.; Coyle, D. Optimizing Layers Improves CNN Generalization and Transfer Learning for Imagined Speech Decoding from EEG. In Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics; 2019. 7.Zhou, A.; Qu, B. Y.; Li, H.; Zhao, S. Z.; Suganthan, P. N.; Zhangd, Q. Multiobjective Evolutionary Algorithms: A Survey of the State of the Art. Swarm and Evolutionary Computation. 2011.

The Doctoral College at Ulster University

Key dates

Submission deadline
Monday 30 October 2023

Interview Date
early November 2023

Preferred student start date
January 2024


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Contact supervisor

Dr Saugat Bhattacharyya

Other supervisors