At a Glance
- Tasks: Design and test innovative AI algorithms for healthcare imaging collaboration.
- Company: Join a leading research group at the Institute of Biomedical Engineering.
- Benefits: Gain valuable experience in a cutting-edge research environment with potential for career growth.
- Other info: Be part of a dynamic team focused on groundbreaking research in AI.
- Why this job: Make a real impact in healthcare by advancing human-AI decision-making.
- Qualifications: PhD/DPhil in machine learning or related fields, with strong publication record.
The predicted salary is between 35000 - 45000 £ per year.
We are looking for a creative and highly motivated postdoctoral researcher to join the new Turing AI World-Leading Fellowship research programme led by Professor Alison Noble. This exciting and ambitious research aims to develop new AI for shared human-AI decision-making in healthcare imaging. Topics in the research programme include single- and multi-modal video-based human-machine collaboration, federated learning for healthcare collaboration and partnership, applied research to understand human skill in healthcare settings, and an investigation of different AI scientist career mobility schemes.
The researcher will be part of the Noble research group at the Institute of Biomedical Engineering, based at the Old Road Campus in Headington. This full-time post is funded by the UKRI and is fixed term for up to 2 years in the first instance.
You will be responsible for the design and testing of machine-learning based algorithms for HAIC. You will work with clinical domain experts to develop tools and evaluate them. The choice of the specific clinical task(s) will be defined in the initial phase of the project which will involve discussions with clinical groups interested in HAIC.
You will hold a relevant PhD/DPhil (or be near completion) in machine learning, computer vision or biomedical image analysis, together with relevant experience. Publications/presentations in top conferences and journals in the discipline of work including as a first author is essential, as well as experience of original deep learning in imaging architecture design and evaluation.
Informal enquiries may be addressed to Professor Alison Noble (alison.noble@eng.ox.ac.uk). For more information about working at the Department, see www.eng.ox.ac.uk/about/work-with-us/. Only online applications received before midday on 10 May 2024 can be considered. You will be required to upload a covering letter/supporting statement, including a brief statement of research interests (describing how past experience and future plans fit with the advertised position), CV and the details of two referees as part of your online application.
The Department holds an Athena Swan Bronze award, highlighting its commitment to promoting women in Science, Engineering and Technology.
Postdoc: Human-AI Collaboration in Healthcare Imaging in Oxford employer: University of Oxford
Join a pioneering research environment at the Institute of Biomedical Engineering, where innovation meets collaboration in the field of healthcare imaging. As part of the Noble research group, you will benefit from a supportive work culture that values creativity and professional growth, alongside access to cutting-edge resources and mentorship from leading experts. With a commitment to diversity and inclusion, exemplified by our Athena Swan Bronze award, we offer a unique opportunity to contribute to impactful research while advancing your career in a vibrant academic setting.
StudySmarter Expert Advice🤫
We think this is how you could land Postdoc: Human-AI Collaboration in Healthcare Imaging in Oxford
✨Tip Number 1
Network like a pro! Reach out to people in the field, especially those connected to the Turing AI programme or Professor Noble's research. A friendly chat can open doors and give you insights that might not be in the job description.
✨Tip Number 2
Show off your skills! Prepare a portfolio of your past work, especially any publications or projects related to machine learning and healthcare imaging. This will help you stand out during interviews and discussions with clinical experts.
✨Tip Number 3
Practice makes perfect! Get ready for potential interviews by rehearsing answers to common questions about your research interests and how they align with the role. We recommend doing mock interviews with friends or colleagues.
✨Tip Number 4
Apply through our website! Make sure to submit your application before the deadline. Tailor your covering letter to highlight how your experience fits the specific needs of the role, and don’t forget to mention your passion for human-AI collaboration!
We think you need these skills to ace Postdoc: Human-AI Collaboration in Healthcare Imaging in Oxford
Some tips for your application 🫡
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Make sure to highlight your research interests and how they align with our exciting work in human-AI collaboration. Be creative and show us your passion for the field!
Tailor Your CV:Don’t just send a generic CV! Tailor it to showcase your relevant experience in machine learning, computer vision, or biomedical image analysis. Highlight your publications and any deep learning projects you've worked on that relate to healthcare imaging.
Showcase Your Research Experience:In your application, emphasise your past research experiences, especially those involving AI and healthcare. We want to see how your skills can contribute to our team and the innovative projects we’re working on.
Apply Online Through Our Website:Remember, the only way to apply is through our website before the deadline! Make sure you upload all required documents, including your covering letter, CV, and referee details. We can’t wait to see your application!
How to prepare for a job interview at University of Oxford
✨Know Your Research Inside Out
Make sure you’re well-versed in the specifics of your past research and how it relates to human-AI collaboration in healthcare imaging. Be ready to discuss your publications and how they demonstrate your expertise in machine learning and computer vision.
✨Prepare for Technical Questions
Expect to dive deep into technical discussions about algorithms and machine-learning techniques. Brush up on your knowledge of federated learning and deep learning architectures, as these are likely to come up during the interview.
✨Show Your Collaborative Spirit
Since this role involves working closely with clinical domain experts, be prepared to discuss your experience in collaborative projects. Highlight any previous teamwork that showcases your ability to communicate complex ideas effectively.
✨Craft a Compelling Research Statement
Your covering letter should not just summarise your CV but also articulate your research interests clearly. Explain how your past experiences align with the goals of the Turing AI Fellowship and what unique perspectives you bring to the table.
