development of Northern Ireland. Our core business activities are teaching and learning, widening access to education, research and innovation and technology and knowledge transfer. - THE ROLE - The postholder will contribute to the anatomical modelling of the trachea and oesophagus using a large dataset of CT scans. The role focuses on medical image processing and image segmentation to isolate these structures and identify key anatomical landmarks. The postholder will develop predictive models to estimate key internal features based on simple clinical parameters such as height, gender, and age. Additionally, they will construct Statistical Shape Models to predict 3D morphological variations from these same clinical parameters. The work supports a broader understanding of patient-specific anatomy, using machine learning techniques to capture population-wide variance. This position offers the opportunity to work with large-scale clinical data and develop expertise in medical image analysis. Due to the short-term nature of this post, the successful candidate must be available to commence immediately and will be required to hold proof of right to work in the UK at the time of application and for the duration of the post. - ABOUT YOU - The postholder will be required to have: - Hold a PhD (awarded or near completion with thesis submitted) in Engineering, Mathematics, Physics, Statistics or a closely related discipline. - Experience in statistical analysis software (e.g., R). - Proficiency in the development of large-scale data analysis pipelines. Please find our employee benefits on our website. Athena Swan Statement The School of Engineering holds a Silver Athena SWAN Award in recognition of our commitment to advancing Gender equality in higher education. You can read more about what this means on our University website. The University has a range of initiatives to support a family friendly working environment, including flexible working. 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.

development of Northern Ireland. Our core business activities are teaching and learning, widening access to education, research and innovation and technology and knowledge transfer. - THE ROLE - The postholder will contribute to the anatomical modelling of the trachea and oesophagus using a large dataset of CT scans. The role focuses on medical image processing and image segmentation to isolate these structures and identify key anatomical landmarks. The postholder will develop predictive models to estimate key internal features based on simple clinical parameters such as height, gender, and age. Additionally, they will construct Statistical Shape Models to predict 3D morphological variations from these same clinical parameters. The work supports a broader understanding of patient-specific anatomy, using machine learning techniques to capture population-wide variance. This position offers the opportunity to work with large-scale clinical data and develop expertise in medical image analysis. Due to the short-term nature of this post, the successful candidate must be available to commence immediately and will be required to hold proof of right to work in the UK at the time of application and for the duration of the post. - ABOUT YOU - The postholder will be required to have: - Hold a PhD (awarded or near completion with thesis submitted) in Engineering, Mathematics, Physics, Statistics or a closely related discipline. - Experience in statistical analysis software (e.g., R). - Proficiency in the development of large-scale data analysis pipelines. Please find our employee benefits on our website. Athena Swan Statement The School of Engineering holds a Silver Athena SWAN Award in recognition of our commitment to advancing Gender equality in higher education. You can read more about what this means on our University website. The University has a range of initiatives to support a family friendly working environment, including flexible working. 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.