Geoscience ML Researcher — Physics‑AI (Remote)

Client Server; Cirencester; Hybrid; GBP 68,000 - 83,000; Full time

Benefits offered by this job

Equity

Hybrid work pattern

3 days WFH per week

Job summary

Client Server in the United Kingdom is seeking a PhD-level Machine Learning Researcher to lead the scientific direction at the intersection of physics and AI. You will design and deploy production-ready models that transform geospatial data into trusted insights for environmental and defence-related applications.

Based near Cirencester, you’ll work in a hybrid setup with 2 days in the office and up to 3 days remote, shaping the research agenda from day one and mentoring others as the team scales.

Qualifications

• PhD or equivalent in ML, Physics, Geophysics, Applied Math or related field.
• Strong research background at intersection of ML and physical modelling (physics-informed AI, surrogate models, differentiable simulation).
• Experience developing ML models for remote sensing or geospatial data.
• Strong Python software engineering skills for reproducible, production-ready research.
• Experience with uncertainty quantification, model validation and explainable AI.

Responsibilities

• Define and shape the scientific direction of the company.
• Lead the intersection of physics and AI to deploy production-ready models.
• Collaborate with Science Lead to design and deploy ML models that handle geospatial data.
• Develop transparent, physics-informed models validated against real-world observations.

Skills

PhD in ML/Physics

Python programming

Remote sensing / geospatial ML

Uncertainty quantification

Explainable AI

Leading technical direction

Mentoring others

Education

PhD or equivalent research experience

Tools

Python

Xarray

Dask

Zarr

STAC

Job description

Client Server in the United Kingdom is seeking a PhD-level Machine Learning Researcher to lead the scientific direction at the intersection of physics and AI. You will design and deploy production-ready models that transform geospatial data into trusted insights for environmental and defence-related applications.

Based near Cirencester, you’ll work in a hybrid setup with 2 days in the office and up to 3 days remote, shaping the research agenda from day one and mentoring others as the team scales.