At a Glance
- Tasks: Develop cutting-edge computational tools in statistics and machine learning.
- Company: Join UCL, a leading university committed to diversity and innovation.
- Benefits: Enjoy 41 days holiday, a pension scheme, and excellent on-site facilities.
- Other info: 8-month funded role with great career development opportunities.
- Why this job: Make a real impact in research while advancing your skills in a supportive environment.
- Qualifications: MSc or PhD in relevant fields required.
The predicted salary is between 39148 - 52586 £ per year.
UCL is seeking a Research Assistant/Fellow in Computational Statistics and Machine Learning to develop skills in mathematical and statistical methodologies. The role, funded for 8 months from January 2027, involves creating computational tools and requires an MSc or PhD in relevant fields.
Salary ranges from £39,148 to £52,586 depending on experience. UCL offers generous benefits including 41 days holiday, a pension scheme, and on-site facilities, emphasizing diversity and equal opportunity.
Research Fellow: Computational Statistics & ML Tools employer: UCL
UCL is an exceptional employer, offering a vibrant work culture that fosters innovation and collaboration in the field of Computational Statistics and Machine Learning. With generous benefits such as 41 days of holiday and a robust pension scheme, UCL prioritises employee well-being and professional growth, making it an ideal place for those seeking meaningful and rewarding employment in a diverse environment.
StudySmarter Expert Advice🤫
We think this is how you could land Research Fellow: Computational Statistics & ML Tools
✨Tap into Online Data Science Communities
Join online communities focused on data science like Kaggle, LinkedIn groups, or Reddit threads. These are goldmines for temporary gigs, as you can network with professionals and potentially hear about opportunities at companies like UCL before they're even advertised!
✨Show Off Your Skills With Projects
Got some cool data science projects? Showcase them on platforms like GitHub or create a personal portfolio website. This visibility is crucial for landing temporary roles—let recruiters see your actual skills in action, which can set you apart from the crowd.
✨Check Out Specialist Job Boards
For temp roles, hit up job boards dedicated to tech and data science, like Stack Overflow Jobs or DataJobs. These platforms often feature openings that you won’t find on general job sites, including contracts with companies like UCL.
✨Leverage University Resources
If you're currently at uni or recently graduated, tap into your school's career services. They often have connections with companies looking for temporary data science interns or contract workers, and they might even host job fairs with employers like UCL.
We think you need these skills to ace Research Fellow: Computational Statistics & ML Tools
Some tips for your application 🫡
Highlight Your Data Projects:When applying for a temporary data science role at UCL, make sure to showcase any relevant projects you've worked on. Whether it's a personal project, an academic undertaking, or contributions to an open-source initiative, detailing these experiences can really set you apart and demonstrate your practical skills.
Emphasise Your Analytical Skills:In your CV and cover letter, focus on the specific analytical skills that are key to data science. Mention any experience with statistical tools, programming languages like Python or R, and data visualisation software. Don't forget to include any certifications that may bolster your expertise!
Show Your Flexibility:Since this is a temporary role, it's important to convey your adaptability and willingness to learn. In your cover letter to UCL, emphasise how quickly you can get up to speed with new tools or projects. Highlight any previous experiences where you've had to adjust to new environments or challenges.
Craft a Unique Data-Driven Cover Letter:Instead of the usual generic cover letter, spice it up with some data! Maybe you’ve improved a process by 20% in a past role or cleaned a dataset with over a million entries. Use these stats to your advantage to grab UCL’s attention and show the tangible impact of your work.
How to prepare for a job interview at UCL
✨Showcase Your Analytical Skills
For a data science gig, it's crucial to demonstrate your analytical abilities. Be ready to discuss previous projects and the methodologies you used. Think about how you can quantify your impact—did your analysis improve efficiency or save costs? These are the stories that will stick with interviewers at UCL.
✨Brush Up on Technical Skills
You might face technical questions on tools relevant to data science, like Python, R, or SQL. Prepare to solve a problem live—perhaps they'll ask you to write a simple query or code snippet. It’s cool to talk about them, but we need to show we can do it in practice, especially in a temporary role where quick results matter.
✨Highlight Your Adaptability
Since this is a temporary position, emphasise your ability to learn quickly and adapt to new tools or workflows. Share examples of how you've thrived in fast-paced environments before, and how you can hit the ground running at UCL.
✨Prepare a Portfolio of Your Work
Bring your portfolio to the table—showcase projects where you've leveraged data science techniques to solve problems. Whether it’s a GitHub repository or a set of case studies, having tangible examples of your work will help you stand out and show what you bring to the team at UCL.
