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- Tasks: Train and evaluate AI models by reviewing clinical scenarios and rating responses.
- Company: Leading UK research organisation at the forefront of medical innovation.
- Benefits: Flexible hours and competitive pay ranging from $80 to $150 per hour.
- Why this job: Make a real impact in healthcare by shaping the future of AI in medicine.
- Qualifications: Must be a verified medical doctor with recent clinical experience.
- Other info: Work remotely with a reliable internet connection in a dynamic research environment.
A leading research organization in the UK is seeking Medical Doctors to train and evaluate innovative AI models. You will review responses to clinical scenarios and rate them for clinical appropriateness.
The role offers flexible hours, with researchers paying between $80 and $150 per hour for your expertise.
Applicants should be verified medical doctors with recent clinical experience and a reliable internet connection.
MDs as Clinical AI Trainer & Model Evaluator employer: Prolific
Contact Detail:
Prolific Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land MDs as Clinical AI Trainer & Model Evaluator
✨Tip Number 1
Network like a pro! Reach out to fellow medical professionals and AI enthusiasts on platforms like LinkedIn. You never know who might have the inside scoop on opportunities or can refer you directly to hiring managers.
✨Tip Number 2
Show off your expertise! When you get the chance to chat with potential employers, highlight your clinical experience and how it relates to AI. Make it clear that you understand both worlds and can bridge the gap between medicine and technology.
✨Tip Number 3
Be proactive! Don’t just wait for job postings to pop up. Reach out to organisations directly, especially those known for innovative AI work in healthcare. A friendly email expressing your interest can go a long way!
✨Tip Number 4
Apply through our website! We’ve got loads of opportunities tailored for medical professionals like you. It’s quick, easy, and ensures your application gets seen by the right people. Don’t miss out!
We think you need these skills to ace MDs as Clinical AI Trainer & Model Evaluator
Some tips for your application 🫡
Show Off Your Medical Expertise: Make sure to highlight your qualifications and recent clinical experience in your application. We want to see how your background makes you the perfect fit for training and evaluating AI models.
Be Clear and Concise: When filling out your application, keep your language straightforward and to the point. We appreciate clarity, so avoid jargon and make it easy for us to understand your skills and experiences.
Tailor Your Application: Don’t just send a generic application! Take the time to tailor your responses to the specific role of Clinical AI Trainer & Model Evaluator. Show us why you’re the best choice for this innovative position.
Apply Through Our Website: We encourage you to apply directly through our website. It’s the easiest way for us to receive your application and ensures you don’t miss any important updates about the process!
How to prepare for a job interview at Prolific
✨Brush Up on Clinical Scenarios
Make sure to review common clinical scenarios and guidelines relevant to your specialty. Being able to discuss these confidently will show your expertise and help you evaluate AI responses effectively.
✨Familiarise Yourself with AI Concepts
While you may not be an AI expert, having a basic understanding of how AI models work and their applications in healthcare can set you apart. This knowledge will help you engage in meaningful discussions during the interview.
✨Prepare Questions for Your Interviewers
Think about what you want to know regarding the role and the organisation. Asking insightful questions not only shows your interest but also helps you determine if this position aligns with your career goals.
✨Highlight Your Recent Clinical Experience
Be ready to discuss your recent clinical experience in detail. Share specific examples of cases you've handled, as this will demonstrate your practical knowledge and ability to evaluate clinical appropriateness in AI responses.
