Research Fellow: Real-Time AI & Wireless Health

Research Fellow: Real-Time AI & Wireless Health

Full-Time 63000 - 77000 £ / year (est.) Home office (partial)
Brunel University of London

At a Glance

  • Tasks: Develop low-latency AI models and collaborate on exciting digital healthcare projects.
  • Company: Brunel University London, a leader in innovative research.
  • Benefits: Generous benefits package and opportunities for publishing at top conferences.
  • Other info: Join a dynamic team and contribute to groundbreaking EU projects.
  • Why this job: Make a real impact in AI and wireless health while working with industry partners.
  • Qualifications: Experience in AI/ML and a passion for digital healthcare.

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

Brunel University London invites applications for a Research Assistant/Research Fellow position to contribute to EU projects funding digital healthcare AI research and wireless communication optimisation. The role entails developing low‑latency AI inference models for markerless pose detection and collaborating with industry partners across the UK/EU. The successful candidate will be involved in publishing findings at top AI/ML conferences and will be supported by a generous benefits package.

Research Fellow: Real-Time AI & Wireless Health employer: Brunel University of London

Brunel University of London is an exceptional employer, offering a dynamic work environment in Uxbridge that fosters academic excellence and innovation. With a strong emphasis on research-driven teaching, employees benefit from generous annual leave, comprehensive training opportunities, and a supportive community that encourages professional growth and collaboration.

Brunel University of London

Contact Details:

Brunel University of London Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land Research Fellow: Real-Time AI & Wireless Health

Get Involved in Data Science Meetups

Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like Brunel University of London!

Show Off Your Projects

Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like Research Fellow: Real-Time AI & Wireless Health at Brunel University of London.

Leverage Professional Networks

Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like Brunel University of London.

Apply Directly through Our Website

When you find a suitable opening like Research Fellow: Real-Time AI & Wireless Health at Brunel University of London, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!

We think you need these skills to ace Research Fellow: Real-Time AI & Wireless Health

AI Inference Models
Markerless Pose Detection
Wireless Communication Optimisation
Collaboration with Industry Partners
Research Publication
Digital Healthcare
Low-Latency Systems

Some tips for your application 🫡

Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!

Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!

Craft a Tailored Cover Letter:For a full-time role at Brunel University of London, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.

Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Brunel University of London. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!

How to prepare for a job interview at Brunel University of London

Brush Up on Your Statistics

For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!

Showcase Your Projects

Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!

Get Comfortable with Python and R

Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at Brunel University of London!

Prepare for Case Studies

Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.