Research Fellow in Computational Modelling & Machine Learning Respiratory Research

Overview

Research Fellow in Computational Modelling & Machine Learning for Respiratory Research

The project will develop a computational framework to identify multi-organ disease from imaging (e.g. computed tomography) and clinical data. The framework will leverage disease progression modelling, unsupervised/semi-supervised learning, and transfer learning to disentangle contributions of individual pathologies to non-specific biomarkers.

The post holder will:

• Collaborate with Dr Joseph Jacob, Dr Alexandra Young, and national and international partners, attending conferences and lab visits.
• Collate, curate, and process relevant data sets; manage data and perform image processing.
• Disseminate research via journal publications, conference presentations, and consortium coordination.
• Design advanced image analysis, modeling, and inference tools for chronic lung diseases.
• Design research proposals, coordinate outreach, engage with funders, and report timely to funders.
• Contribute to teaching, mentor junior researchers, and support multidisciplinary projects.
• Adhere to UCL policies, quality assurance, and departmental activities such as seminars and public events.

• PhD required for Grade 7 (or Grade 6B if not yet awarded).
• Senior level (5+ years of experience).
• Experience in data processing, data management, and image processing desirable.
• Knowledge of disease progression modeling, unsupervised/semi-supervised learning, and transfer learning.

• Grade 7 appointment contingent on PhD award; otherwise appointed Grade 6B (salary £39,148 – £40,85 per annum).
• Salary backdated to the date of final PhD thesis submission at Grade 7.
• Funding period until 31 October 2027 (first instance).

International travel for conferences and dataset access is expected.

UCL