Research Associate

About the role

We seek a motivated postdoctoral research assistant (0.5 FTE, 24 months) to lead advanced analysis of functional near‑infrared spectroscopy (fNIRS) data within the Clinical Neuroergonomics Programme. The postholder will analyse multimodal datasets collected from clinical and operational populations performing realistic and high‑stakes tasks, with the aim of improving understanding of cognitive workload, team dynamics, and physiological resilience in real and simulated environments.

What you would be doing

The post-holder will be responsible for analysis of the following datasets:

• Surgical team datasets: fNIRS recordings from surgeons, anaesthetists and theatre staff during simulated laparoscopic procedures (e.g., simulated laparoscopic appendicectomy). Datasets include task markers, video annotation, behavioural performance metrics, and complementary physiological signals (ECG, respiration) and eye tracking.
• Critical care datasets: fNIRS data from anaesthetists and critical care doctors performing central venous catheter access and other procedure simulations under differing task demands and team configurations; includes timing logs, subjective workload measures, and performance outcomes.
• Field‑work datasets: fNIRS from engineers and technical staff performing operational tasks in field conditions, including experiments under heat stress and environmental perturbations; data include environmental measures (temperature, humidity), accelerometery/motion sensors, and task performance metrics.
• Resting‑state and baseline recordings across participant groups for comparative and connectivity analyses.
• Multimodal and repeated‑measures datasets enabling within‑subject comparisons, learning/adaptation analyses, and predictive modelling of performance and safety outcomes

What we are looking for

An experienced person with the following essential background:

• PhD (awarded or near completion) in Neuroscience, Biomedical Engineering, Neuroimaging, Cognitive Science, Signal Processing, Computer Science or related discipline.
• Strong demonstrable background in advanced statistics and signal processing.
• Demonstrable experience analysing human fNIRS data across the full pipeline: acquisition QA, preprocessing (motion/artifact correction, physiological noise removal, short‑channel regression), and haemodynamic modelling (GLM, deconvolution).
• Experience of working with Shared Near-Infrared Spectroscopy format (.snirf) the standardized, open-source file format developed by the fNIRS community (SfNIRS) to store, organize, and share functional near-infrared spectroscopy data
• Advanced analysis experience including SPM‑OT / NIRS‑SPM (or equivalent), Homer2/Homer3, nirs‑toolbox, MNE‑NIRS or comparable toolkits.
• Proficiency with source reconstruction/optical forward–inverse modelling and connectivity/network analyses (seed/ICA, coherence, phase measures, graph metrics).
• Please see full list of requirements on the job specification

What we can offer you

• The opportunity to continue your career at a world-leading institution and be part of our mission to use science for humanity.
• Benefit from a sector-leading salary and remuneration package (including 41 days’ annual leave and generous pension schemes).
• Access to a range of workplace benefits including a flexible working policy from day one, generous family leave packages, on-site leisure facilities and cycle-to-work scheme.
• Interest-free season ticket loan schemes for travel.
• Be part of a diverse, inclusive and collaborative work culture with various staff networks and resources to support your personal and professional wellbeing.

Further Information

This role is on a 0.5 FTE fixed-term contract for 2 years.

*Candidates who have not yet been officially awarded their PhD will be appointed as a Research Assistant within the salary range £43,863 - £47,223 per annum.

If you require any further details about the role, please contact either Professor Daniel Leff d.leff@imperial.ac.uk or Dr Felipe Orihuela-Espina f.orihuela-espina@bham.ac.uk