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- Tasks: Support research on diagnostic algorithms for asthma using AI and machine learning.
- Company: Join a world-leading institution focused on science for humanity.
- Benefits: Sector-leading salary, 41 days off, generous pension, and professional development opportunities.
- Other info: Full-time role with potential for renewal; start by September 2026.
- Why this job: Make a real impact in healthcare while growing your career in a collaborative environment.
- Qualifications: MSc in relevant field and proficiency in Python; experience with biomedical datasets required.
The predicted salary is between 43863 - 47223 £ per year.
The candidate will support a research program focusing on developing diagnostic algorithms for asthma using allergic sensitisation data. The project uses Machine Learning and AI to analyse high-dimensional clinical, immunological and omics data-sets in respiratory and allergic diseases.
What you would be doing:
- You must be organised, highly self-motivated, and possess excellent communication, interpersonal, and computing skills.
- You will be expected to manage your time and performance effectively and demonstrate a proactive, knowledgeable approach, with the ability to solve complex analytical problems supported by robust data management practices.
- You should demonstrate a high degree of proficiency in one or more statistical or programming environments (e.g., Python, MATLAB, or R).
- You should also have experience preparing clear oral and written reports of research findings.
What we are looking for:
- You must hold an MSc in Statistics, Machine Learning, Artificial Intelligence, Data Science, or another relevant quantitative discipline with a strong statistical or machine learning component.
- Demonstrated experience in the analysis of large, high-dimensional biomedical datasets.
- Proficiency with Python, MATLAB or R.
- 2-3 years' experience of complex clinical, immunological, or omics datasets.
- Experience implementing computational pipelines for integrated analysis of clinical and laboratory data, including data harmonisation.
- Experience dealing with real-world clinical data issues, including missing data, measurement variability, and data heterogeneity.
- Experience building and validating predictive models.
- Strong knowledge of multivariate statistics and machine learning, and network analytics.
- Knowledge of principles of reproducible research, data quality control, and good analytical practice.
What we can offer you:
- Relevant training and professional development will be encouraged through both internal opportunities and external courses and seminars.
- The opportunity to attend and present at conferences.
- Sector-leading salary and remuneration package (including 41 days off a year and generous pension schemes).
- Be part of a diverse, inclusive and collaborative work culture with various staff networks and resources designed to support your personal and professional wellbeing.
- The opportunity to continue your career at a world-leading institution and be part of our mission to use science for humanity.
- Grow in your career with tailored training programmes for academic staff including dedicated support with navigating your career and managing research as well as a transparent promotion process.
This role is for a full-time (35h) and a fixed term contract for 18 months, in the first instance, with the possibility of renewal. This is a full-time post must start no later than September 2026.
For any questions or details about the role, please contact Sabrina Kapur.
Research Assistant in Data Sciences - London employer: Imperial College London
Contact Detail:
Imperial College London Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Research Assistant in Data Sciences - London
✨Tip Number 1
Network like a pro! Reach out to people in your field, attend relevant events, and connect with researchers at Imperial. You never know who might have the inside scoop on job openings or can put in a good word for you.
✨Tip Number 2
Show off your skills! Prepare a portfolio showcasing your projects, especially those involving Python, MATLAB, or R. This will give potential employers a taste of what you can do and how you tackle complex data challenges.
✨Tip Number 3
Practice makes perfect! Get ready for interviews by rehearsing answers to common questions about your experience with high-dimensional datasets and machine learning. The more comfortable you are, the better you'll perform.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets seen. Plus, it shows you're genuinely interested in joining our team at StudySmarter and contributing to our mission.
We think you need these skills to ace Research Assistant in Data Sciences - London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the role of Research Assistant in Data Sciences. Highlight your experience with statistical programming and any relevant projects you've worked on, especially those involving high-dimensional datasets.
Craft a Compelling Cover Letter: Your cover letter should tell us why you're the perfect fit for this role. Share specific examples of your work with machine learning and data analysis, and express your enthusiasm for contributing to asthma research.
Showcase Your Skills: Don’t forget to mention your proficiency in Python, MATLAB, or R. We want to see how you’ve used these tools in real-world scenarios, so include any relevant projects or experiences that demonstrate your skills.
Apply Through Our Website: To make sure your application gets to us, apply through our website. It’s the best way to ensure we receive all your details correctly and can consider you for this exciting opportunity!
How to prepare for a job interview at Imperial College London
✨Know Your Data Inside Out
Make sure you’re well-versed in the specifics of high-dimensional biomedical datasets. Brush up on your experience with Python, MATLAB, or R, and be ready to discuss how you've tackled real-world data issues like missing data or measurement variability.
✨Showcase Your Problem-Solving Skills
Prepare examples that highlight your analytical problem-solving abilities. Think about times when you’ve built or validated predictive models and how you approached complex analytical challenges. This will demonstrate your proactive and knowledgeable approach.
✨Communicate Clearly and Effectively
Since excellent communication skills are a must, practice explaining your research findings clearly and concisely. Be prepared to present your work as if you were at a conference, focusing on clarity and engagement to showcase your interpersonal skills.
✨Emphasise Your Organisational Skills
Being organised is key for this role. Prepare to discuss how you manage your time and performance effectively. Share strategies you use to stay on top of tasks and ensure that you meet deadlines, especially when dealing with complex datasets.