Senior Data Assimilation Scientist at Spire
Glasgow, GB

Spire Global is a 150-person space data company founded in 2012. In less than six years, Spire has built one of the world's largest satellite constellations, and we're just getting started.

We are looking for a Senior Data Assimilation (DA) Scientist to join our Glasgow office. The Senior Data Assimilation Scientist will lead a small but agile team tasked with assimilating new and existing global total electron content (TEC) data into an ionosphere model in order to improve the accuracy of GNSS location-based services and other applications.

Positioning errors from ionospheric effects on GNSS signals remain one of the last hurdles in improving GNSS-based positioning accuracies. Spire satellites have the unique capability to globally measure TEC and scintillation indices and provide near real-time estimates of ionospheric delay and disturbance effects on GNSS services. The Senior Data Assimilation Scientist will help build Spire’s capability to assimilate Spire satellite TEC measurements, as well as external sources of ionospheric data, into Spire’s in-house ionosphere model.

This capability will enable Spire to provide near real-time corrections to GNSS location-based services and their providers, leading to greater confidence in applications that require high accuracy and resiliency, such as autonomous vehicle navigation. You will have opportunities to work with top-level scientists at Spire as well as scientists from around the world on issues that matter.

Responsibilities of your role:

  • The successful candidate will work will lead the Spire Ionosphere DA team and work to implement and evaluate cutting-edge DA methods and assimilate large amounts of GNSS-TEC and other satellite and ground-based data into Spire’s ionosphere model.
  • Proposing and implementing innovative approaches to data acquisition, data processing, and quality control.
  • Implementing cutting-edge capabilities for assimilating satellite data into the associated ionosphere model.
  • Working with the software engineering team to define the most effective software solutions.
  • Presenting research findings at scientific conferences or workshops.

Qualifications / Experience:

  • Applicants must have either an MS or PhD degree in Meteorology, Atmospheric Science, Mathematics, or equivalent working experience in DA methods.
  • Working experience with statistical model optimisation and machine learning techniques.
  • Working experience with DA systems involving state-of-the-art ionosphere models.
  • Working experience with cutting-edge DA methods, such as 3D-Var, 4D-Var, ensemble Kalman filter, and hybrid ensemble-variational methods.
  • Working knowledge of Fortran, C, C++, Python, Linux scripting and code management practices.
  • Working experience with statistical models and statistical inference.
  • Knowledge of optimal control theory and minimisation methods is desirable.
  • Demonstration of enthusiasm and ability to work in a development team that never stops improving DA methods and results.

Strong candidates will also possess skills in one or more of the following areas:

  • Understanding of ionospheric physics and the importance of TEC data for navigation and positioning accuracy.
  • Knowledge and research experience in ionospheric science or space weather.
  • Understanding of research and techniques in processing TEC data.
  • Experience of using satellite data in modelling techniques.