Researcher in Environmental Model Emulation – Deadline 31 October 2021

The British Antarctic Survey are looking for a Climate Storyline Analyst to assist on the UKRI-BAS work required for Work Package 1 of the EU Horizon 2020 funded research project Polar Regions in the Earth System: Role of local regional scale processes in the changing polar and global climate systems (PolarRES).

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.


The post holder will develop and apply emulation software for environmental simulators to tackle some specific science challenges selected from the interdisciplinary environmental activities of the British Antarctic Survey ( In addition, the successful candidates will join the AI Lab’s ongoing activities, working as part of a team, to create a framework to underpin AI-based and physics-informed Digital Twins of the natural environment. The successful candidate will work in close collaboration with our partner organisations, including: The Alan Turing Institute; international research institutes; our University network; and our two Centres for Doctoral Training (CDTs) in Earth Observation and AI for Environmental Risk. Candidates will have experience working in machine learning and/or data science.


A PhD or equivalent experience in a relevant field


  • To develop machine learning and/or model emulation methods for environmental prediction, scientific understanding, planning and/or monitoring;
  • To conduct outstanding, creative and innovative research in AI for environmental science, and to develop significant outcomes through publications.
  • To work collaboratively with researchers and senior investigators from across BAS, and external partners;
  • To champion reproducible science and open-source infrastructure to empower the global environmental research community;
  • To advise masters-level, and PhD students on machine learning methods
  • To represent BAS to key stakeholders, such as funding agencies and Government;
  • To disseminate research to both academic and non-academic audiences (including public engagement), contribute to the external visibility of the BAS AI Lab;
  • Seek ways to develop societal impact;
  • To play an active role in advancing the BAS AI Lab;
  • To help create a friendly and approachable community of environmentally-focused machine learning experts and facilitate integration with the BAS science and engineering teams;
    Some delivery of training activities may be required to support the development of AI methods across BAS research disciplines;
  • Undertake other duties as appropriate as requested by the BAS Director.

The above list is not exhaustive, and the job holder is required to undertake such duties as may reasonably be requested within the scope of the post. All employees are required to act professionally, co-operatively and flexibly in line with the requirements of the post and UKRI

Please quote reference for any queries: BAS 21/139
Publication date: 08 October 2021
Closing date for receipt of application forms is: 31 October 2021
Interviews are scheduled to be held on: 17 November 2021

Communication skills

  • Track record of engaging with partners from different domains of expertise; – Essential
  • Excellent written and verbal communication skills, including experience in the visual representation of quantitative data, the authoring of research papers or technical reports, and giving presentations or training on technical subjects; – Essential
  • Ability to communicate more complex, specialist, or conceptual information clearly and persuasively. – Essential
  • Effective communicator and networker within and outside the research community (creating networks); – Desirable [1]

Computer / IT skills

  • Excellent computer skills – Essential
  • Proficiency in one or more modern statistical programming languages used in research in data science and machine learning, such as Python or Julia – Essential
  • Experience of working with large datasets and writing scalable code – Essential
  • Experience in computational statistics, particularly Bayesian modelling and Bayesian statistics – Desirable [4]
  • Contribution and engagement with open-source software communities – Desirable [4]

Decision Making

  • Record of successful decisions made working collaboratively – Essential

Interpersonal skills

  • Commitment to professional development of their own career; – Essential
  • Willingness to act as mentor for others; – Essential
  • Ability to interpret and share knowledge by advising and guiding others as required. – Essential
  • Ability to foster an innovative and creative environment for research – Desirable [2]

Other Factors

  • Proven record of ongoing development of their technical skills and knowledge; – Essential
  • Flexible attitude towards work. – Essential
  • An understanding of the importance of good practice for producing reliable software and reproducible research (e.g. version control, Jupyter notebooks); – Desirable [2]
  • An interest in methodological advances in environmental sciences – Desirable [1]


  • A PhD or equivalent experience in a relevant field – Essential

Resource Management ability

  • Experience in managing, structuring, and analyzing research data – Essential
  • Ability to lead one’s own work independently, and collaborate productively as part of a team, in order to meet milestones and deadlines. – Essential

Skills / Experience

  • Expertise in state-of-the-art methods in data science and computational intelligence; – Essential
  • Ability to lead on developing and writing papers in the application of machine learning; – Essential
  • Ability to rapidly assimilate new ideas and techniques on the job and apply them successfully; – Essential
  • Ability to work and interact professionally within a team of researchers and students. – Essential
  • Track-record on leading papers – Desirable [1]

For application and further information, please follow this link.

via BAS
Have any news or opportunity in ocean sciences to share? Send it to