Machine Learning Data Scientist for Land Modelling Industrial Placement 2026 in Exeter
Machine Learning Data Scientist for Land Modelling Industrial Placement 2026

Machine Learning Data Scientist for Land Modelling Industrial Placement 2026 in Exeter

Exeter Placement 22700 - 30000 £ / year (est.) No home office possible
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At a Glance

  • Tasks: Develop machine learning techniques for land surface modelling and improve computational performance.
  • Company: Join the Met Office, a leader in environmental science and innovation.
  • Benefits: Competitive salary, 27.5 days annual leave, and discounts on shopping.
  • Why this job: Make a real impact on global challenges while gaining hands-on experience.
  • Qualifications: Studying a STEM degree with programming experience, ideally in Python.
  • Other info: Collaborative environment with mentoring from experts and excellent career networking opportunities.

The predicted salary is between 22700 - 30000 £ per year.

The Met Office is delighted to open our advertising for Industrial Placements 2026. This is an exciting opportunity to join the Met Office on a 12-month Year in Industry placement, commencing at the start of July 2026. You will develop your skills and knowledge and ensure you gain the most value possible from your experience with us. You will have the opportunity to network with our cohort of Industrial Placements all over the Met Office and understand what career opportunities are on offer at the Met Office after you graduate.

As our Machine Learning Data Scientist for Land Modelling Industrial Placement 2026, the job may be suitable for hybrid working, which is where an employee works part of the week in the office and part of the week from home. This is a voluntary, non-contractual arrangement and the location advertised will be your contractual place of work. As an Industrial Placement, we would expect you to attend the office once a week as a minimum. Our opportunity is full time, 37 hours per week. Our people are at the heart of what we do and we’ll do our best to agree a working pattern that works for everyone.

World changing work: We’re a force for good – focusing on our environmental and social impact. We’re experts by nature – always learning and developing to do things better. We live and breathe it – putting our purpose at the heart of decision‑making. We’re better together – understanding partnerships and inclusivity make us greater. We keep evolving – pushing boundaries to make tomorrow better for our customers.

Our Industrial Placement scheme offers ambitious and capable undergraduates the opportunity to gain valuable experience working alongside diverse and highly skilled experts in their field. You’ll be working on projects that really matter and will make a difference. We are offering an exciting opportunity for a highly motivated undergraduate student to spend a year working on the development of machine learning approaches for land surface modelling. The successful candidate will join the team working with the Joint UK Land Environment Simulator (JULES) – a leading community land surface model used in weather, climate, hydrology, and environmental science. The project will focus on exploring ways in which machine learning can be applied to speed up aspects of JULES while maintaining its physical realism. By combining the strengths of traditional physics‑based models with innovative data‑driven techniques, the aim of this Industrial Placement is to develop more efficient and accurate representations of the land within the Earth system.

This placement provides hands‑on experience at the intersection of environmental science, machine learning, and high‑performance computing, and is ideal for students interested in applying computational methods to tackle global challenges. You will join a team of parameterisation developers in Atmospheric Processes and Parametrisations (APP), working in a collaborative and supportive environment. The placement will provide on‑the‑job training to broaden your expertise, alongside mentoring from experts in land surface modelling and machine learning. This is a valuable opportunity to apply and develop your technical skills on real‑world scientific challenges, while gaining professional experience and building networks for your future career.

  • Assist in developing and testing machine learning techniques to improve the computational performance of JULES.
  • Support the identification of model components where ML can provide acceleration.
  • Work with scientists and software developers to integrate ML approaches into existing workflows.
  • Contribute to project documentation, reporting, and (where appropriate) publications or presentations.

Your package includes:

  • Your salary will be £27,170
  • Annual Leave starting at 27.5 days
  • Access to discounted shopping, inclusive of retail, leisure and lifestyle brands

Essential Criteria, skills and experience:

  • You must be studying for an undergraduate degree with a strong background in a STEM subject e.g., data sciences, applied mathematics, physical sciences or computing.
  • You have some experience of scientific programming, ideally with Python.
  • You can demonstrate you have an understanding of applying machine learning or computational techniques.
  • You can demonstrate you have strong problem‑solving skills and a willingness to learn new methods for environmental applications.
  • You have excellent verbal and written communication reflecting an ability to listen, engage and clearly communicate with a varied audience, and to facilitate good teamwork.

How to apply: In the position you’ll be based in the Met Office headquarters in Birmingham. For more details and the application process, please contact careers@metoffice.gov.uk. Closure date: 23:59 7th December 2025. Interviews will be completed by February 2026. We recruit on merit, fairness, and open competition in line with the Civil Service Code. We can only accept applications from those eligible to live and work in the UK - please refer to GOV.UK for information. We require Security clearance, for which you need to have resided in the UK for at least 3 of the last 5 years, 2 of these years must be immediately preceding the point of your application. You will need to achieve full security clearance within your first 6 months with us.

Machine Learning Data Scientist for Land Modelling Industrial Placement 2026 in Exeter employer: Met Office

The Met Office is an exceptional employer, offering a unique opportunity for undergraduates to engage in meaningful work that contributes to environmental science and machine learning. With a strong focus on employee development, collaborative culture, and flexible working arrangements, you will gain invaluable experience while being supported by experts in the field. Located in Birmingham, you will enjoy a vibrant city atmosphere alongside access to professional growth and networking opportunities.
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Contact Detail:

Met Office Recruiting Team

StudySmarter Expert Advice 🤫

We think this is how you could land Machine Learning Data Scientist for Land Modelling Industrial Placement 2026 in Exeter

✨Tip Number 1

Network like a pro! Reach out to current or past interns at the Met Office on LinkedIn. Ask them about their experiences and any tips they might have for landing the Machine Learning Data Scientist role.

✨Tip Number 2

Prepare for your interview by brushing up on your Python skills and machine learning concepts. We recommend doing some mock interviews with friends or using online platforms to get comfortable with common questions.

✨Tip Number 3

Show your passion for environmental science! When you get the chance, share your thoughts on how machine learning can tackle global challenges. This will help you stand out as someone who truly cares about the work.

✨Tip Number 4

Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, keep an eye on job alerts so you don’t miss out on any opportunities that pop up.

We think you need these skills to ace Machine Learning Data Scientist for Land Modelling Industrial Placement 2026 in Exeter

Machine Learning
Scientific Programming
Python
Data Sciences
Applied Mathematics
Physical Sciences
Computational Techniques
Problem-Solving Skills
Communication Skills
Teamwork
Environmental Applications
High-Performance Computing
Model Integration
Project Documentation

Some tips for your application 🫡

Tailor Your CV: Make sure your CV is tailored to the Machine Learning Data Scientist role. Highlight relevant skills, experiences, and projects that align with the job description. We want to see how your background fits into our world-changing work!

Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to express your passion for machine learning and environmental science. Tell us why you’re excited about this placement and how you can contribute to our team at the Met Office.

Showcase Your Skills: Don’t forget to showcase your programming skills, especially in Python, and any experience with machine learning techniques. We’re looking for problem solvers who are eager to learn, so make sure to highlight those abilities!

Apply Through Our Website: We encourage you to apply through our website for a smooth application process. It’s the best way to ensure your application gets to us directly. Plus, you’ll find all the details you need right there!

How to prepare for a job interview at Met Office

✨Know Your Stuff

Make sure you brush up on your machine learning concepts and the specifics of land surface modelling. Familiarise yourself with JULES and how machine learning can enhance its performance. This will show your genuine interest and understanding of the role.

✨Showcase Your Skills

Prepare to discuss your experience with scientific programming, especially in Python. Have examples ready that demonstrate your problem-solving skills and any projects where you've applied machine learning techniques. This will help you stand out as a candidate who can hit the ground running.

✨Communicate Clearly

Since teamwork is key in this role, practice articulating your thoughts clearly and concisely. Be ready to explain complex ideas in simple terms, as you'll need to engage with a varied audience. Good communication can set you apart from other candidates.

✨Ask Insightful Questions

Prepare thoughtful questions about the team, the projects you'll be working on, and the impact of your work. This shows your enthusiasm for the position and helps you gauge if the company culture aligns with your values, especially their focus on environmental impact and collaboration.

Machine Learning Data Scientist for Land Modelling Industrial Placement 2026 in Exeter
Met Office
Location: Exeter
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  • Machine Learning Data Scientist for Land Modelling Industrial Placement 2026 in Exeter

    Exeter
    Placement
    22700 - 30000 £ / year (est.)
  • M

    Met Office

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