Overview
Research Fellow in Computational Modelling & Machine Learning for Respiratory Research
The project will develop a computational framework to identify multiorgan 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.
Responsibilities
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.
Qualifications
- 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.
Appointment Details
- 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).
Location and Travel
International travel for conferences and dataset access is expected.
Company
UCL
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Research Fellow in Computational Modelling & Machine Learning for Respiratory Research
The project will develop a computational framework to identify multiorgan 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.
Responsibilities
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.
Qualifications
- 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.
Appointment Details
- 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).
Location and Travel
International travel for conferences and dataset access is expected.
Company
UCL
#J-18808-Ljbffr…