At a Glance
- Tasks: Develop and test AI models for fetal ultrasound imaging to assist clinical teams.
- Company: Join King’s College London, collaborating with NHS and industry leaders.
- Benefits: Fixed-term contract, professional development days, and a supportive research environment.
- Other info: Opportunity to publish research and present at conferences.
- Why this job: Make a real impact in medical AI and improve healthcare outcomes.
- Qualifications: PhD in medical AI or related field, strong communication, and organisational skills.
The predicted salary is between 40000 - 50000 € per year.
Project Overview: This research aims to develop and test machine learning models that can recognise specific imaging planes acquired during the first trimester fetal ultrasound scan. This will be the first step in developing an AI‑powered tool that can be used clinically to assist sonographers in undertaking these scans. The role will be based at King’s College London, working closely with clinical teams at Guy’s & St Thomas’ NHS Foundation Trust. The project includes collaboration with NHS partners and industry stakeholders to ensure that the reporting interface is technically robust, clinically usable and ready for translation into routine practice.
About the Role: The specific aim of the post will be to train machine learning models to detect and classify specific imaging planes using our pre‑existing dataset of fetal ultrasound scans. A range of machine learning approaches will need to be tested.
- Develop and test machine learning models designed to identify specific image planes corresponding to particular fetal organs, from a stream of ultrasound video data.
- Work independently on defined research packages while consulting with the PI and collaborators as needed.
- Contribute to the planning, design, and management of new and ongoing project components.
- Collaborate effectively with internal and external partners.
- Stay up to date with relevant scientific literature in medical AI.
- Lead and contribute to writing high‑quality scientific publications.
- Present findings at conferences and group meetings.
- Maintain accurate and reproducible records of research activities.
- Support training and supervision of students or junior team members.
- Participate in routine responsibilities such as data handling, code documentation, and ensuring safe working practices in the lab.
- Contribute to teaching activities when requested.
This is a full‑time post (35 hours per week), and you will be offered a fixed‑term contract until 31st May 2027. Research staff at King’s are entitled to at least 10 days per year (pro‑rata) for professional development. This entitlement applies to Postdocs, Research Assistants, Research and Teaching Technicians, Teaching Fellows and AEP equivalent up to and including grade 7.
About You: To be successful in this role, we look for candidates with the following skills and experience:
Essential Criteria:- PhD awarded (or pending) including work on medical AI applied to ultrasound.
- Strong background in medical AI model training and testing, with experience of AI applied to fetal ultrasound.
- Ability to work independently.
- Excellent communication skills.
- Strong organisational skills, with the ability to manage tasks independently, meet deadlines and work calmly under pressure.
- Track record of written publications and presentations at conferences.
- Knowledge of medical imaging, particularly ultrasound, and/or familiarity with DICOM and clinical imaging workflows.
- Experience with standard software engineering practices, including version control systems (e.g. Git), software testing methodologies and collaborative code development.
Equality and Diversity: The Equality Act 2010 protects the rights of our students and staff and provides a framework to fulfil our duties to eliminate unlawful discrimination, harassment and victimisation and to advance equality of opportunity.
Research Associate in Medical Artificial Intelligence employer: King’s College London
At King’s College London, we pride ourselves on being an exceptional employer that fosters a collaborative and innovative work culture. As a Research Associate in Medical Artificial Intelligence, you will have access to extensive professional development opportunities, including dedicated time for training and the chance to contribute to impactful research alongside leading clinical teams at Guy’s & St Thomas’ NHS Foundation Trust. Our commitment to equality and diversity ensures a supportive environment where your contributions are valued, making this role not just a job, but a meaningful career path in advancing medical technology.
StudySmarter Expert Advice🤫
We think this is how you could land Research Associate in Medical Artificial Intelligence
✨Network Like a Pro
Get out there and connect with people in the medical AI field! Attend conferences, workshops, or even local meetups. We can’t stress enough how important it is to build relationships; you never know who might have a lead on your dream job.
✨Show Off Your Skills
When you get the chance, showcase your work! Whether it's through presentations at conferences or sharing your research online, let your expertise shine. We want to see you making an impact in the community, and it could catch the eye of potential employers.
✨Tailor Your Approach
Don’t just send out generic applications. Research the companies and roles you’re interested in, and tailor your approach accordingly. We recommend highlighting your relevant experience in medical AI and ultrasound to make your application stand out.
✨Apply Through Our Website
Make sure to apply directly through our website for the best chance at landing that role! We keep everything streamlined, and it shows us you’re genuinely interested in being part of our team. Plus, it’s super easy to navigate!
We think you need these skills to ace Research Associate in Medical Artificial Intelligence
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to the role of Research Associate in Medical AI. Highlight your experience with machine learning models, especially in medical imaging and ultrasound. We want to see how your skills align with our project goals!
Craft a Compelling Cover Letter:Your cover letter should tell us why you're passionate about medical AI and how your background makes you a great fit for this role. Be sure to mention any relevant projects or publications that showcase your expertise. Let your personality shine through!
Showcase Your Communication Skills:Since collaboration is key in this role, demonstrate your excellent communication skills in your application. Whether it's through your writing style or by mentioning past teamwork experiences, we want to know how you can effectively work with others.
Apply Through Our Website:Don't forget to apply through our website! It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it shows you’re keen on joining our team at StudySmarter!
How to prepare for a job interview at King’s College London
✨Know Your Stuff
Make sure you brush up on your knowledge of medical AI, especially as it relates to ultrasound. Be ready to discuss specific machine learning models you've worked with and how they can be applied to fetal imaging. This shows you're not just familiar with the theory but have practical experience too.
✨Showcase Your Communication Skills
Since you'll be collaborating with clinical teams and presenting findings, it's crucial to demonstrate your communication skills during the interview. Practice explaining complex concepts in simple terms, and be prepared to discuss how you've effectively communicated your research in the past.
✨Prepare for Technical Questions
Expect some technical questions about machine learning approaches and software engineering practices. Brush up on your knowledge of DICOM, version control systems like Git, and any relevant coding languages. Being able to confidently answer these questions will set you apart from other candidates.
✨Highlight Your Organisational Skills
This role requires strong organisational skills, so be ready to share examples of how you've managed tasks independently and met deadlines in previous projects. Discuss any tools or methods you use to stay organised, as this will show that you can handle the responsibilities of the position.
