Find a job 
Featured Companies 
Featured Universities 
For Companies At a Glance
- Tasks: Develop data engineering and hybrid modelling tools for battery technologies.
- Company: Leading UK university with a focus on innovative research.
- Benefits: Competitive salary, potential progression, and a full-time role until 2028.
- Why this job: Join a cutting-edge project and make a real impact in battery technology.
- Qualifications: PhD in a related field and strong programming skills, especially in Python.
- Other info: Exciting opportunity to work in a dynamic research environment.
The predicted salary is between 36636 - 46049 £ per year.
A leading UK university is seeking a Research Fellow in Birmingham to contribute to the FAST project focused on battery technologies. The role involves developing data engineering and hybrid modelling tools to enhance battery formation processes.
Applicants should have a PhD in a related field and strong programming skills, particularly in Python and machine learning.
Salary ranges from £36,636 to £46,049 with potential progression. This is a full-time, fixed-term position until September 2028.
Battery Data Scientist & Hybrid Modelling Fellow employer: The University of Birmingham
Contact Detail:
The University of Birmingham Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Battery Data Scientist & Hybrid Modelling Fellow
✨Tip Number 1
Network like a pro! Reach out to current or former employees at the university or in the battery tech field. A friendly chat can give us insider info and maybe even a referral!
✨Tip Number 2
Show off your skills! Prepare a portfolio or GitHub repository showcasing your Python projects and machine learning models. This will help us stand out during interviews and demonstrate our expertise.
✨Tip Number 3
Practice makes perfect! Get ready for technical interviews by brushing up on data engineering concepts and hybrid modelling techniques. We can even do mock interviews with friends to build confidence.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets noticed. Plus, we can tailor our CV and cover letter to match the job description perfectly.
We think you need these skills to ace Battery Data Scientist & Hybrid Modelling Fellow
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your relevant experience in battery technologies and data engineering. We want to see how your skills align with the FAST project, so don’t hold back on showcasing your programming prowess, especially in Python!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you’re passionate about battery technologies and how your background makes you a perfect fit for this role. We love seeing enthusiasm and a clear connection to the job description.
Showcase Your Projects: If you've worked on any projects related to hybrid modelling or machine learning, make sure to mention them! We’re keen to see practical examples of your work that demonstrate your skills and creativity in tackling complex problems.
Apply Through Our Website: Don’t forget to submit your application through our website! It’s the best way for us to receive your materials and ensures you’re considered for the position. Plus, it’s super easy to do!
How to prepare for a job interview at The University of Birmingham
✨Know Your Stuff
Make sure you brush up on the latest developments in battery technologies and hybrid modelling. Familiarise yourself with the FAST project and be ready to discuss how your PhD research aligns with their goals.
✨Show Off Your Skills
Prepare to demonstrate your programming prowess, especially in Python and machine learning. Have examples ready that showcase your experience in developing data engineering tools or any relevant projects you've worked on.
✨Ask Smart Questions
Think of insightful questions about the role and the team. This shows your genuine interest in the position and helps you understand how you can contribute to the project's success.
✨Practice Makes Perfect
Conduct mock interviews with a friend or mentor. Focus on articulating your thoughts clearly and confidently, especially when discussing complex topics like battery formation processes and modelling techniques.