Geoscience ML Researcher - Remote 3 Days/Week, Equity

Client Server Limited

Cirencester

Hybrid

GBP 45,000 - 75,000

Full time

2 days ago
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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

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

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