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Institution
Trinity College Dublin
Vacancy Category
Research
Salary From
€33 791
Contract Type
Temporary
Vacancy closing date
15 Jun, 2026
Reference
039154
Subject / Area
Biological Sciences
Computer Science
Health and Medical
Mathematics and Statistics
Other
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Part-time Research Assistant (50%) – Neural Signal analysis

Post Status: Specific Purpose Contract – Part-time 50% FTE 

Research Group / Department / School: NeuroMotor group, Academic Unit of Neurology, School of Medicine, Trinity College Dublin, the University of Dublin 

Location: Trinity Biomedical Sciences Institute, Trinity College Dublin, the University of Dublin College Green, Dublin D02 R590, Ireland

Reports to: Asst. Prof Bahman Nasseroleslami, Dr Marjorie Metzger, Prof Orla Hardiman 

Salary: Salary pro‑rata at 50% of the approved Research Assistant Salary Scale, starting at Irish Universities Association (IUA) Point 1 (€33,791 per annum) in line with Government Pay Policy. 

Hours of Work: 19.5 hours per week (50% of a 39-hour full-time working week) 

Closing Date: 12 Noon (GMT), Friday 15th June 2026

 

Post Summary

Role overview 

The Research Assistant will support studies investigating how motor neuron diseases (MNDs) affect brain network dynamics using high‑density EEG. Responsibilities include data collection, preprocessing, and quantitative signal analysis to characterise large‑scale neural network activity. By integrating neurophysiological measures with neuropsychological and functional assessments, the post‑holder will contribute to the identification of EEG‑based candidate biomarkers that quantify neural alterations. The role involves applying data‑driven analysis approaches, including statistical and machine learning methods, to support disease classification and patient stratification, while maintaining a strong focus on neurobiological interpretation and clinical relevance. 

 

Research context 

The team is seeking a Research Assistant to support cutting‑edge research within a multidisciplinary group specialising in neuroengineering, neural signal processing, computational analysis, psychology and neurology. The role involves high‑quality data collection and the development of robust, reproducible analysis pipelines for neurophysiological datasets, ensuring high ethical standards, clinical relevance, and participant well‑being. The group fosters international and interdisciplinary collaborations to advance quantitative and computational research on MNDs. 

 

Research Group 

The NeuroMotor group, led by Dr. Bahman Nasseroleslami within the Academic Unit of Neurology (headed by Professor Orla Hardiman), focuses on developing biomarkers of functional and cognitive decline in MND and other neurological conditions. The group employs neurophysiological experiments, advanced neural signal analysis, computational and statistical modelling, clinical phenotyping, and multimodal data integration. The Academic Unit of Neurology is a multidisciplinary research team comprising neural engineers, clinicians, neuroscientists, neuropsychologists, geneticists, and other specialists. The unit collaborates closely with Beaumont and St. James’s Hospitals in Dublin, as well as national and international research groups. 

 

Project Focus 

This role offers an opportunity to contribute to EEG‑based biomarker development and patient stratification for MND, based on functional network analysis in a clinically grounded research environment.

 

Person Specification 

The ideal candidate will have demonstrated competency in performing data analyses (e.g. statistics, machine learning, signal analysis) and programming, and preferably will have research experience in areas such as neurophysiology, neurology, medical informatics/statistics (to a BSc. or MSc. level). Beginners welcome. 

 

Qualifications 

A Bachelor's or Master's degree in Neuroscience, Biology, Physiology, Biomedical Engineering, Electrical Engineering, Computer Science, Data Science, or a related field. Experience or coursework in signal processing, neuroimaging, or computational neuroscience is highly desirable. 

Familiarity with clinical research and working with human participants is a plus.

 

Application Instructions

Please click on the Apply button below for the full job description and application instructions.

 

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