Research Associate Deep learning and Fetal Neurosonography

University of Oxford; Oxford; On-site; GBP 34,000 - 44,000; Full time

Job summary

A leading academic institution is seeking a postdoctoral research associate to join its prestigious Department of Computer Science. This role will involve advanced research in deep learning, specifically focusing on high-performance techniques for neural imaging applications. The successful candidate will have the opportunity to work alongside experts in the field, contributing to innovative solutions that advance medical imaging practices. A PhD in a relevant field and strong programming skills are essential.

Benefits

Contributory pension scheme

38 days annual leave

Comprehensive childcare services

Family leave schemes

Cycle loan scheme

Discounted travel options

Qualifications

• Strong research skills in deep learning and computer vision.
• Experience in implementing network designs and GPU optimization.
• Ability to contribute to multidisciplinary research projects.

Responsibilities

• Develop high-performance deep learning algorithms for medical imaging.
• Contribute to advancements in neural implicit reconstruction techniques.
• Collaborate with a multidisciplinary team to enhance prenatal imaging.

Skills

Deep Learning

Computer Vision

Neural Rendering

CUDA Programming

Education

PhD in Computer Science or related field

Job description

A postdoctoral research associate position is available for a technically strong researcher to join the Oxford Machine Learning in NeuroImaging (OMNI) lab at Oxford's Department of Computer Science, focusing on high-performance deep learning for neural implicit reconstruction of ultrasound data. The goal is to advance the scalability and efficiency of neural radiance fields (NeRFs) and related architectures to enable near real-time 3D reconstruction from 2D ultrasound video.

The post-holder will contribute to cutting-edge research at the intersection of deep learning, computer vision, and biomedical imaging. This includes exploring efficient network designs, contributing to the development of novel learning-based representations for geometric reconstruction, and integrating insights from neural rendering into medical imaging workflows. A major focus will be on accelerating inference and training using GPU-optimised components, including custom CUDA kernels.

This role offers a unique opportunity to push the boundaries of neural scene representations in a medical imaging context. The successful candidate will work alongside a multidisciplinary team of deep learning researchers, computer vision experts, and clinicians, designing scalable and responsive tools that directly support prenatal brain imaging at the bedside. The candidate will also benefit from co-supervision by Dr Joao Henriques from the Visual Geometry Group (VGG).

The successful applicant will report to the project PI, Professor Ana Namburete. The position is available from September.

Flexible working

This is a full-time role (37.5 hours per week) that requires on-site working. Some flexibility may be possible, depending on work needs, such as attending in-person meetings or travelling for conferences.

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 September 2025. Interviews are expected to be held in October.

Contact Person :

HR Coordinator

Vacancy ID :

180964

Contact Phone :

Closing Date & Time :

29-Sep-2025 12:00

Pay Scale :

RESEARCH GRADE 7

Contact Email :

[e-mail]

Salary (£) :

Grade 07RS: £38,674-£43,171 per annum inclusive of Oxford University weighting Potential to under fill at grade 06RS: £34,982-£40,855 per annum inclusive of Oxford University weighting