At a Glance
- Tasks: Design and test machine-learning algorithms for human-AI collaboration in healthcare imaging.
- Company: Join a leading research group at the Institute of Biomedical Engineering.
- Benefits: Fixed-term position with funding from UKRI and opportunities for impactful research.
- Other info: Be part of a dynamic team with a commitment to diversity and inclusion.
- Why this job: Contribute to groundbreaking AI research that enhances decision-making in healthcare.
- Qualifications: PhD/DPhil in machine learning, computer vision, or biomedical image analysis required.
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
- 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. 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.
Postdoctoral Research Assistant in Human-AI Collaboration employer: University of Oxford
Joining the Institute of Biomedical Engineering as a Postdoctoral Research Assistant offers an exceptional opportunity to engage in pioneering research at the forefront of Human-AI collaboration in healthcare. With a strong emphasis on innovation and collaboration, the institute fosters a supportive work culture that encourages professional growth through access to world-class resources and mentorship from leading experts like Professor Alison Noble. Located at the vibrant Old Road Campus in Headington, employees benefit from a dynamic environment that promotes interdisciplinary partnerships and a commitment to diversity, exemplified by the Department's Athena Swan Bronze award.
StudySmarter Expert Advice🤫
We think this is how you could land Postdoctoral Research Assistant in Human-AI Collaboration
✨Tip Number 1
Network like a pro! Reach out to current or former researchers in the field, especially those connected to Professor Alison Noble. A friendly chat can give you insights and might even lead to a recommendation.
✨Tip Number 2
Show off your skills! Prepare a portfolio of your past projects, especially those related to machine learning and healthcare imaging. This will help you stand out during interviews and discussions.
✨Tip Number 3
Stay updated on the latest trends in AI and healthcare. Being knowledgeable about recent advancements can spark engaging conversations with interviewers and show your passion for the field.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets seen. Plus, it shows you’re serious about joining our team at the Institute of Biomedical Engineering.
We think you need these skills to ace Postdoctoral Research Assistant in Human-AI Collaboration
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 projects in human-AI collaboration. Keep it engaging and personal, showing us why you're the perfect fit for our team.
Showcase Your Experience:When detailing your CV, focus on your relevant experience in machine learning and biomedical image analysis. Don’t forget to mention any publications or presentations you've led, as we love to see your contributions to the field!
Tailor Your Application:Make sure to tailor your application to the specific role. Highlight your skills in designing and testing algorithms, and how you’ve collaborated with clinical experts in the past. This will show us that you understand the role and are ready to hit the ground running!
Apply Online Before the Deadline:Remember, we only accept online applications submitted before midday on 10 May 2024. So, don’t leave it to the last minute! Head over to our website to submit your application and join us in this groundbreaking research journey.
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. Be ready to discuss your publications and how they contribute to the field, especially in healthcare imaging.
✨Prepare for Technical Questions
Expect questions about machine learning algorithms and their applications in clinical settings. Brush up on your knowledge of deep learning architectures and be prepared to explain your design choices and evaluation methods.
✨Show Your Collaborative Spirit
Since you'll be working with clinical domain experts, highlight your teamwork skills. Share examples of past collaborations and how you’ve successfully communicated complex ideas to non-technical stakeholders.
✨Articulate Your Future Vision
Be ready to discuss your research interests and how they align with the goals of the Turing AI World-Leading Fellowship. Show enthusiasm for the project and articulate how you see your role contributing to the advancement of human-AI decision-making in healthcare.
