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, with experience in echocardiography.
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.
Contact Professor Alison Noble
Contact email alison.noble@eng.ox.ac.uk
Postdoctoral Research Assistant in Fetal Ultrasound Biomarker Discovery Closing date: May 22, 2026 in Oxford 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 expertise, you will be well-supported in your career development within a prestigious academic environment.
StudySmarter Expert Advice🤫
We think this is how you could land Postdoctoral Research Assistant in Fetal Ultrasound Biomarker Discovery Closing date: May 22, 2026 in Oxford
✨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. You never know who might have the inside scoop on job openings!
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your previous work in machine learning and fetal echocardiography. This could be anything from research papers to projects you've worked on. Having tangible evidence of your expertise can really set you apart during interviews.
✨Tip Number 3
Prepare for those interviews! Research the CAIFE study and understand its goals. Be ready to discuss how your background aligns with their mission. Practise common interview questions and think about how you can demonstrate your problem-solving skills in real-world scenarios.
✨Tip Number 4
Apply through our website! We make it super easy for you to submit your application. Plus, it shows you're genuinely interested in joining our team. Don’t forget to tailor your application to highlight your relevant experience in fetal heart scans and machine learning methods!
We think you need these skills to ace Postdoctoral Research Assistant in Fetal Ultrasound Biomarker Discovery Closing date: May 22, 2026 in Oxford
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to the role. Highlight your relevant experience in medical video analysis or computer vision, and don’t forget to mention any work with echocardiography. We want to see how your skills align with our exciting project!
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 your background makes you a great fit for our team. Keep it engaging and personal – we love to see your enthusiasm!
Showcase Your Research Experience:In your application, be sure to showcase any previous research projects, especially those involving machine learning or AI. We’re looking for creativity and motivation, so share examples that demonstrate your innovative thinking and problem-solving skills.
Apply Through Our Website:Don’t forget to apply through our website! It’s the best way to ensure your application gets to us directly. Plus, you’ll find all the details you need about the role and our team there. We can’t wait to hear from you!
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 current advancements in AI technology for detecting congenital heart conditions, as well as any recent publications from the team. This will show your genuine interest and help you engage in meaningful discussions during the interview.
✨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 highlight your skills in developing algorithms or working with echocardiography data. Be ready to explain your thought process and how you approach problem-solving in a collaborative environment.
✨Ask Insightful Questions
Think of questions that demonstrate your curiosity about the role and the team dynamics. Inquire about the specific challenges they face in biomarker discovery or how they envision the collaboration between researchers and clinical experts. This not only shows your enthusiasm but also helps you gauge if the position is the right fit for you.
✨Emphasise Teamwork and Collaboration
Since this role involves working in a small interdisciplinary team, be prepared to discuss your experiences in collaborative settings. Share examples of how you’ve successfully worked with others to achieve common goals, especially in research contexts. Highlighting your ability to communicate effectively with clinical experts will be a plus!
