Radiology AI Research Scientist, Foundation Models (Remote)

Radiology AI Research Scientist, Foundation Models (Remote)

Full-Time 63000 - 77000 £ / year (est.) Hybrid
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At a Glance

  • Tasks: Design innovative AI models and run experiments in radiology.
  • Company: Join DeepHealth, a leader in AI research with global partnerships.
  • Benefits: Flexible remote work, competitive salary, and opportunities for mentorship.
  • Other info: Collaborate with top institutions like Imperial College London in a dynamic environment.
  • Why this job: Make a real impact in healthcare by translating research into clinical solutions.
  • Qualifications: Experience in AI research and a passion for mentoring others.

The predicted salary is between 63000 - 77000 £ per year.

Deep Health seeks a Senior Research Scientist to advance foundation models in radiology AI within the ML Capabilities team.

You will design novel architectures, run experiments, and translate research into deployable clinical solutions in collaboration with Imperial College London.

You will mentor researchers, publish work, and help set the scientific roadmap while working in a hybrid/remote environment across international partners.

Radiology AI Research Scientist, Foundation Models (Remote) employer: DeepHealth

DeepHealth is an exceptional employer that champions innovation and collaboration within a supportive remote work environment. With a strong focus on employee growth, we offer opportunities for professional development in cutting-edge technologies like AWS and Kubernetes, ensuring our team members thrive in their careers while contributing to meaningful projects. Join us to be part of a dynamic culture that values creativity and teamwork, all from the comfort of your home in the UK.

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Contact Details:

DeepHealth Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land Radiology AI Research Scientist, Foundation Models (Remote)

✨Join Local Tech Meetups

Get out there and mingle with fellow developers by joining local tech meetups. It’s a fantastic way to meet people who might be working at DeepHealth or know someone who does. Plus, you can pick up some trendy tech skills and trends while you're at it!

✨Contribute to Open Source Projects

Show off your coding chops by jumping into open-source projects. Not only does this give you practical experience, but it also gets you noticed in the dev community. You'll create a killer portfolio that speaks volumes about your skills to DeepHealth.

✨Tap into Online Developer Communities

Don’t underestimate the power of online developer communities like GitHub, Stack Overflow, and even Reddit. Participate in discussions, share your projects, and build your visibility. We can often find opportunities through these channels that can lead to a full-time gig at companies like DeepHealth.

✨Explore Job Boards Specifically for Tech Roles

Keep your eyes peeled on job boards that focus on tech roles. Sites like TechCareers or Stack Overflow Jobs can often have listings for companies like DeepHealth that might not show up on broader job sites. Make it a habit to check these regularly, and don’t hesitate to apply directly through our website!

We think you need these skills to ace Radiology AI Research Scientist, Foundation Models (Remote)

Machine Learning
Deep Learning
Research Design
Architectural Design
Experimental Design
Clinical Solution Development
Mentoring

Some tips for your application 🫡

Show off your coding skills:When applying for a software engineering role, it's super important to showcase your coding skills. Make sure your CV includes your tech stack, any relevant programming languages you’re comfortable with, and examples of projects you've worked on. If you have a GitHub profile, link it up! We love to see code in action.

Tailor your portfolio:For a full-time role, we’d expect to see some solid examples of your work in your portfolio. Make sure to include at least two or three projects that highlight your problem-solving skills and your ability to work with different technologies. Focus on the projects that are most relevant to the position at DeepHealth.

Craft a killer cover letter:Your cover letter is your chance to stand out—make it personal! Explain why you want to work at DeepHealth and how your skills align with the role. Show us your passion for software development. We dig enthusiastic candidates who understand the value of collaboration and continuous learning!

Be clear and concise:When it comes to writing your CV and cover letter, clarity is key. Avoid jargon that could confuse us and stick to simple, direct language. Highlight your achievements with quantifiable results where possible, and keep everything easy to read. A well-organised application goes a long way!

How to prepare for a job interview at DeepHealth

✨Brush Up on Your Coding Skills

For a full-time software engineering role, it's crucial that we stay sharp with our coding abilities. Expect technical questions that might involve solving problems on the spot or discussing algorithms. Practise on platforms like LeetCode or HackerRank to get comfortable with the types of questions that often come up.

✨Know Your Tools and Frameworks

Make sure we’re well-acquainted with the tools and technologies listed in the job description. Familiarise ourselves with any specific frameworks or programming languages mentioned. If DeepHealth uses React or Node.js, for instance, be ready to discuss how we’ve used them in previous projects or coursework.

✨Showcase Your Projects

Bring along a portfolio that highlights our best work. This could be code samples, GitHub repositories, or any side projects we’ve built. Make sure we can talk through our thought process for each project, especially the challenges we faced and how we solved them—this shows our problem-solving skills in action.

✨Prepare for Behavioural Questions

While technical skills are key, full-time positions also require cultural fit. Be ready to discuss our previous experiences and how we handle teamwork, conflict, and deadlines. Brush up on the STAR method—Situation, Task, Action, Result—to clearly articulate our past experiences when discussing how we've contributed to a team.