Research Associate in Neural Rendering and Medical Image Reconstruction Full-time NEW

Research Associate in Neural Rendering and Medical Image Reconstruction

We are looking for a postdoctoral research associate position available in the Oxford Machine Learning in Neuroimaging (OMNI) lab at Oxford's Department of Computer Science. The post-holder will report directly to Professor Ana Namburete and will work within a multidisciplinary team of deep learning researchers, research software engineers, and obstetricians, and will collaborate with Dr João Henriques (Visual Geometry Group, VGG) and Professor Aris Papageorghiou (Nuffield Department of Women's and Reproductive Health).

The project focuses on efficient neural implicit representations and neural rendering methods for volumetric reconstruction from freehand ultrasound sweeps acquired with handheld probes. The overarching goal is to enable near-real-time 3D reconstruction at the bedside, supporting quantitative assessment of fetal brain development in low-resource settings.

The post-holder will develop machine learning and neural scene representation methods for reconstructing 3D fetal brain volumes from handheld ultrasound video, and integrate these algorithms into interactive clinical imaging workflows. They will contribute to research at the intersection of 3D computer vision, neural rendering, and medical image analysis. This includes developing scalable 2D-to-3D reconstruction architectures and working with ultrasound acquisition systems to deliver interactive feedback during scanning.

Flexible working. The successful candidate will work onsite in the Department of Computer Science buildings in central Oxford, however remote and flexible working can be considered.

What We Offer

As an employer, we genuinely care about our employees' wellbeing and this is reflected in the range of benefits that we offer including:

• An excellent contributory pension scheme
• 38 days annual leave (pro-rata for part-time roles)
• A comprehensive range of childcare services
• Family leave schemes
• Cycle loan scheme
• Discounted bus travel and Season Ticket travel loans
• Membership to a variety of social and sports clubs

Diversity

Committed to equality and valuing diversity.

Application Process

You will be required to upload a supporting statement and an up-to-date CV as part of your online application. Your supporting statement must clearly demonstrate how you meet each of the essential selection criteria listed in the job description. Applications that do not include a supporting statement or CV, or fail to address the criteria in sufficient detail, will not be considered.

While we recognise the value of AI tools in assisting with application preparation, submissions that are clearly AI-generated without personalisation or insight will be rejected. It's crucial that your application reflects your own experiences and understanding of the role.

The closing date for applications is noon on 29th June 2026. Interviews are expected to be held in July.