At a Glance
- Tasks: Design and test innovative AI methods for fetal heart biomarker discovery.
- Company: Join a leading research team at Oxford University focused on groundbreaking medical technology.
- Benefits: Competitive salary, collaborative environment, and the chance to make a real difference in healthcare.
- Other info: Work in a dynamic, interdisciplinary team with excellent career development opportunities.
- Why this job: Be part of an exciting project that uses AI to improve fetal health outcomes.
- Qualifications: PhD in medical video analysis or computer vision; experience with echocardiography is a plus.
The predicted salary is between 39424 - 47779 € per year.
We are seeking a creative and highly motivated postdoctoral researcher to join the CAIFE study, a joint project led by Professor Alison Noble (Institute of Biomedical Engineering) and Professor Aris Papageorghiou (Department of Women’s and Reproductive Health). This exciting and ambitious research aims to develop new AI‑assistive technology for detecting congenital heart conditions (CHDs) from fetal heart scans. The Oxford team, in partnership with five hospital sites, has curated a large fetal echocardiography dataset called CAIFE consisting of both healthy and abnormal fetal heart scans.
In this role you will be responsible for the design and testing of original machine‑learning based methods for fetal heart biomarker discovery from the CAIFE image and video dataset. The full‑time position is funded by InnoHK and is fixed‑term for 12 months. You will be working in a small highly motivated interdisciplinary team working towards a shared goal. You will design and pilot test image and video‑based CHD biomarkers, and work closely with clinical domain experts to define and evaluate AI models.
Responsibilities- Design and pilot testing of original image and video‑based CHD biomarkers.
- Develop machine‑learning methods for fetal heart biomarker discovery from the CAIFE dataset.
- Collaborate with clinical experts to define and evaluate AI models.
- Relevant PhD/DPhil (or near completion) in medical video analysis or computer vision with a video focus.
- Prior experience in working with echocardiography or fetal echocardiography, or related experience on real‑world video analysis.
Postdoctoral Research Assistant in Fetal Ultrasound Biomarker Discovery Closing date: May 22, 2026 employer: University of Oxford
As a Postdoctoral Research Assistant in Fetal Ultrasound Biomarker Discovery at Oxford University, you will be part of a pioneering team dedicated to advancing healthcare through innovative AI technology. The collaborative and interdisciplinary work culture fosters creativity and professional growth, while the opportunity to contribute to meaningful research in fetal health makes this role particularly rewarding. With access to extensive resources and support from leading experts in the field, you will be well-positioned to make a significant impact in medical research.
StudySmarter Expert Advice🤫
We think this is how you could land Postdoctoral Research Assistant in Fetal Ultrasound Biomarker Discovery Closing date: May 22, 2026
✨Tip Number 1
Network like a pro! Reach out to your connections in the field of medical video analysis or AI. Attend relevant conferences or webinars, and don’t be shy about introducing yourself to potential collaborators or mentors.
✨Tip Number 2
Showcase your skills! Create a portfolio that highlights your previous work in machine learning and fetal echocardiography. This could be anything from research papers to projects you've worked on. Make sure it’s easily accessible online.
✨Tip Number 3
Prepare for interviews by brushing up on your knowledge of AI models and their application in healthcare. Be ready to discuss how you would approach designing and testing biomarkers, as well as your experience with the CAIFE dataset.
✨Tip Number 4
Apply through our website! We’ve got a streamlined process that makes it easy for you to submit your application. Plus, it shows you’re serious about joining our team and contributing to groundbreaking research.
We think you need these skills to ace Postdoctoral Research Assistant in Fetal Ultrasound Biomarker Discovery Closing date: May 22, 2026
Some tips for your application 🫡
Tailor Your CV:Make sure your CV highlights your relevant experience in medical video analysis or computer vision. We want to see how your skills align with the exciting work we're doing at StudySmarter, so don’t hold back on showcasing your achievements!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you're passionate about fetal ultrasound biomarker discovery and how you can contribute to our team. Keep it engaging and personal – we love to see your personality come through.
Showcase Your Research Experience:Since this role involves designing and testing original methods, make sure to detail any relevant research projects you've worked on. We’re keen to know about your hands-on experience with echocardiography or similar fields, so be specific!
Apply Through Our Website:We encourage you to apply directly through our website for a smoother application process. It’s the best way to ensure your application gets into the right hands, and we can’t wait to see what you bring to the table!
How to prepare for a job interview at University of Oxford
✨Know Your Research Inside Out
Make sure you’re well-versed in the CAIFE study and its objectives. Familiarise yourself with the latest advancements in AI technology for detecting congenital heart conditions, as well as any relevant literature on fetal echocardiography. This will not only show your enthusiasm but also your commitment to the role.
✨Showcase Your Technical Skills
Prepare to discuss your experience with machine learning and video analysis in detail. Bring examples of past projects or research that demonstrate your ability to design and test original methods. Be ready to explain your thought process and how you approach problem-solving in a collaborative environment.
✨Engage with Clinical Experts
Since collaboration with clinical domain experts is key, think about how you can effectively communicate complex technical concepts to non-technical team members. Prepare questions that show your interest in their expertise and how you can work together to achieve the project goals.
✨Be Ready for Scenario-Based Questions
Expect to face scenario-based questions that assess your critical thinking and adaptability. Think about potential challenges in developing biomarkers from the CAIFE dataset and how you would address them. This will help demonstrate your proactive mindset and readiness to tackle real-world problems.
