Ionospheric Scientist

British Antarctic Survey (BAS)

Postdoctorate Position 3 years Cambridge, UK

Uploaded 26 Oct 2021

Job Description


The British Antarctic Survey (BAS) are looking for an Ionospheric Scientist.

The mesosphere/lower thermosphere is a critical boundary between the climate system and the space weather regime. It is the least understood part of our atmosphere. In order to accurately predict impacts of space weather and climate variability on the whole atmosphere we need an accurate representation of the whole atmosphere.
‘MesoS2D: Mesospheric sub-seasonal to decadal predictability’ is a NERC funded £2.3M project led by BAS to study the mesosphere/thermosphere above Scandinavia, a highly instrumented region. The overall aim of the project is to improve our understanding of mesosphere/lower thermosphere dynamics and providing a pathway for improved prediction of the Earth atmospheric system.

Who we are

British Antarctic Survey (BAS) delivers and enables world-leading interdisciplinary research in the Polar Regions. Its skilled science and support staff based in Cambridge, Antarctica and the Arctic, work together to deliver research that uses the Polar Regions to advance our understanding of Earth as a sustainable planet. Through its extensive logistic capability and know-how BAS facilitates access for the British and international science community to the UK polar research operation. Numerous national and international collaborations, combined with an excellent infrastructure help sustain a world-leading position for the UK in Antarctic affairs.

British Antarctic Survey is a component of the Natural Environment Research Council (NERC). NERC is part of UK Research and Innovation We employ experts from many different professions to carry out our Science as well as to keep the lights on, feed the research and support teams, and keep everyone safe! If you are looking for an opportunity to work with amazing people in amazing places, then British Antarctic Survey could be for you. We aim to attract the best people for those jobs.


  • Scientific analysis of ionospheric radar (EISCAT) data in support of the MesoS2D grant.
  • Working with large amounts of data to study the variability of the lower ionosphere in response to many different space weather and atmospheric drivers across a wide range of temporal scales.
  • Collaborating with the team in comparing the data with model outputs in order to identify where models need improvement to properly capture mesosphere/lower thermosphere/ionosphere region.

Person Specification

Communication skills - a) oral skills b) written skills

  • Proficient in written and spoken English - Essential
  • Good presentation skills for dissemination of results - Essential
  • Ability to easily communicate with an expert audience, both written and oral - Desirable [2]
  • Ability to communicate science to a non-expert audience - Desirable [2]

Computer / IT skills

  • Experiences in a data analysis language, e.g., MATLAB, PYTHON, etc - Essential
  • Knowledge of MATLAB and PYTHON. - Desirable [1]
  • Experience of using GIT or similar version control - Desirable [1]
  • Experience with a UNIX type environment (e.g., LINUX) including command-line knowledge - Desirable [1]
  • Record of publications in peer reviewed literature - Desirable [2]

Decision Making

  • Good problem-solving skills - Essential

Interpersonal skills

  • Can work with others in a team - Essential
  • Can work well individually and under direction - Essential

Managerial ability

  • Able to meet objectives and work to specified deadlines - Essential

Numerical ability

  • Advanced numerical skills - Essential
  • Understanding of basic statistical analysis - Essential
  • Understanding of multiparameter regression - Desirable [2]


  • A PhD in physics, maths, or associated discipline (e.g. atmospheric, environmental science). - Essential

Skills / Experience

  • Experience of data handling - Essential
  • Knowledge of radar theory - Desirable [1]
  • Experience of handling large data sets - Desirable [1]