Machine Learning Researcher - Geoscience

Client Server Limited; Cirencester; Hybrid; GBP 45,000 - 75,000; Full time

Benefits offered by this job

Equity

Hybrid work

Remote work 3 days/week

Job summary

Client Server Limited in the UK seeks a PhD-level Machine Learning Researcher to shape the scientific direction of our geoscience platform. You will design and deploy production-ready models that combine physics-based modelling with AI to analyse satellite and geospatial data.

Based in Cirencester, you’ll join a well-funded start-up with equity and a flexible hybrid policy, including 3 days at home. You’ll lead research initiatives and mentor others as we scale our AI for environmental and

Qualifications

• PhD or equivalent research experience in ML, Physics, Geophysics, Applied Mathematics or related field.
• Strong research background at the intersection of machine learning and physical modelling, e.g. physics-informed AI, surrogate models, neural operators, differentiable simulation or data assimilation.
• Experience developing ML models for remote sensing, Earth observation or geospatial data.

Responsibilities

• Define and lead the scientific direction for production-grade ML models combining physics-based and data-driven approaches.
• Collaborate with the Science Lead to design and deploy production-ready models on geospatial data.
• Mentor others and influence future scientific hires as the company scales.

Skills

Python software engineering

Uncertainty quantification

Explainable AI

Remote sensing data familiarity

Leadership/mentoring

Education

PhD or equivalent research experience in ML/Physics/Geophysics/Applied Mathematics

Tools

Xarray

Dask

Zarr

STAC

Job description

Machine Learning Researcher - Geoscience

Machine Learning Researcher (PhD Python AI) nr. Cirencester to £75k

Are you a PhD educated Machine Learning Research Scientist looking to apply your research to one of the world's most important environmental challenges?

You could be progressing your career at a well funded start-up developing an AI powered intelligence platform that transforms satellite imagery and scientific data into actionable insights about the Arctic. Combining cutting edge machine learning with physics based modelling, the team is tackling problems with real-world impact on climate, infrastructure and global decision-making (please note this is used for Defence clients as well as environmental).

Your role:

As the first senior Machine Learning Research Scientist, you'll play a pivotal role in defining the company's scientific direction, leading the intersection of physics and AI.

Collaborating with the Science Lead, you'll design and deploy production ready machine learning models that transform complex geospatial and remote sensing data into trusted, explainable insights. Rather than relying on black-box AI, you'll develop physics informed models that are transparent, scientifically rigorous and validated against real world observations.

This is a rare opportunity to shape the research agenda from day one, influence future scientific hires and see your work deployed into production rather than remaining in academic papers.

Location:

You'll be based in a beautiful Cotswolds (near Cirencester) office, with stunning views and a range of facilities including free parking onsite (not commutable on public transport) two days a week with flexibility to work from home the other three days.

About You

• You have achieved a PhD (or equivalent research experience) in Machine Learning, Physics, Geophysics, Applied Mathematics, Computational Science or a related discipline
• You have a strong research background at the intersection of machine learning and physical modelling, such as physics informed AI, surrogate models, neural operators, differentiable simulation or data assimilation
• You have experience of developing ML models for remote sensing, Earth observation, geospatial data or other scientific datasets
• You have strong Python software engineering skills with a focus on reproducible, production quality research
• You have experience with uncertainty quantification, model validation and explainable AI
• You're comfortable leading technical direction, working autonomously and mentoring others
• Experience with cryosphere science, climate modelling, glaciology, atmospheric science or the Pangeo ecosystem (Xarray, Dask, Zarr, STAC) would be highly advantageous but isn't essential

What's in it for You?

• Salary to £75k
• Equity
• X3 days work from home per week
• Impactful role with great career progression as the company scales