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Environmental Scientist - Algal Blooms & Remote Sensing

Posted 19 days 10 hours ago by Amelia Space Technologies

Permanent
Part Time
Engineering Jobs
London, United Kingdom
Job Description

London, United Kingdom Posted on 16/06/2026

Amelia Space Technologies is building a planetary intelligence platform that turns Earth observation data into clear, actionable answers for the people managing our environment. One of our capabilities is detecting and forecasting harmful algal blooms (HABs) from satellite data for water companies, utilities, regulators, and environmental bodies.

The Role

We are looking for an expert in algae, harmful algal blooms, cyanobacteria, and the remote sensing of water quality. You'll be our scientific and environmental specialist, making sure that what we detect, forecast, and report is rigorous, defensible, and genuinely useful to the organisations that rely on it. This is a contractor role, part-time or full-time.

Role Description :

  • Develop highly accurate algal bloom detection and early-warning capabilities.
  • Validate and strengthen our scientific methodology, so every output we put in front of a customer stands up to technical scrutiny.
  • Quantify confidence and uncertainty in our outputs, so customers know how much to trust each result.
  • Shape our HAB monitoring offering into a market-leading service, and lend scientific credibility to conversations with water-sector clients.

What you bring

  • Deep sector expertise in freshwater and/or marine algae and cyanobacteria: the biology, the drivers of blooms, and what the data really means.
  • Hands-on experience with remote sensing and Earth observation of water quality.
  • Qualifications in phycology, aquatic/freshwater ecology, limnology, marine biology, environmental science, oceanography, or remote sensing.
  • The ability to explain complex science simply, for decision-makers who aren't scientists.

Ideal Qualifications

  • Proficiency with remote sensing and geospatial tools (e.g., satellite imagery analysis, GIS, Python or R for environmental data, image classification, time-series analysis).
  • A deep understanding of the drivers of harmful algal blooms: nutrient dynamics, temperature, and hydrological influences across limnology, coastal, or marine ecology.
  • Familiarity with the regulatory and monitoring context water organisations operate in (e.g., bathing water, drinking water safety, Environment Agency standards).
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