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: Collaborative environment with a focus on career development and innovation.
- 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, 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. 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 employer: University of Oxford
Join a pioneering research environment at the Institute of Biomedical Engineering, where innovation meets collaboration in 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 in the field. 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
✨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 just set you apart.
✨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 demonstrate your expertise and passion during interviews.
✨Tip Number 3
Practice makes perfect! Get comfortable discussing your research interests and how they align with the role. Mock interviews with friends or mentors can help you articulate your thoughts clearly and confidently.
✨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 and contributing to groundbreaking research in human-AI collaboration.
We think you need these skills to ace Postdoc: Human-AI Collaboration in Healthcare Imaging
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 – we want to see your passion for the field!
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, especially as a first author, as this will really catch our eye!
Tailor Your Application:Make sure to tailor your application to the specific role. Refer to the job description and highlight how your skills and experiences make you a perfect fit for the postdoc position in our innovative research programme.
Submit Online Before the Deadline:Remember, we only accept online applications! Make sure to submit everything before midday on 10 May 2024. Double-check that you’ve included all required documents, like your CV, cover letter, and referee details, to avoid any last-minute hiccups.
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.
✨Engage with Clinical Applications
Since you'll be working closely with clinical domain experts, show your understanding of healthcare settings. Prepare examples of how your work can translate into practical tools for clinicians, and think about potential clinical tasks you could tackle in the project.
✨Demonstrate Your Collaborative Spirit
This role involves teamwork, so highlight your experience in collaborative projects. Share specific instances where you’ve successfully worked with others, especially in interdisciplinary teams, to develop and evaluate algorithms or tools.
✨Prepare Thoughtful Questions
Interviews are a two-way street! Prepare insightful questions about the research programme, the team dynamics, and future directions of the project. This shows your genuine interest and helps you assess if the role is the right fit for you.
