- Job reference:
- BAS 20/45
- Contract type:
- Full Time
- Fixed-Term Appointment for 12 months.
- Starting salary from £30,782 per annum.
- We offer generous benefits
- British Antarctic Survey
- Closing date:
- 22 March, 2020 11:59 pm
The British Antarctic Survey’s AI Lab is offering a unique opportunity as a Data Scientist.
What is about?
The role involves applying machine learning tools to reduce uncertainties in future water security.
Who are we ?
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 www.ukri.org
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 British Antarctic Survey (BAS) has recently established an Artificial Intelligence (AI) Lab (https://www.bas.ac.uk/ai) to foster the application of various machine learning (and adjacent) techniques to the rapidly growing, complex, and heterogeneous body of data found in atmospheric, oceanic, and Earth sciences
The purpose of this job is to work with environmental scientists and engineers within the AI Lab and BAS to apply machine learning algorithms to detect changes in Himalayan glaciers and impacts on water security.
A PhD in a quantitative subject (or equivalent)
- Exploring and pre-processing available satellite, model and in situ datasets on the distribution and variability of Himalayan glacier ice and precipitation, including large N-dimensional gridded products
- Applying and optimising machine learning algorithms
- Liaising with BAS environmental scientists and machine learning engineers at The Alan Turing Institute (ATI)
- Develop proof-of-concept studies to help support large grant proposals
- To publish papers, either as the lead author or as co-author
- Manage code on GitHub (or equivalent)
- Any other duties as required by the Director
Please quote reference: BAS 20/45
Closing date for receipt of application forms is: 22 March 2020
Interviews are scheduled to be held: 31 March 2020
Starting date: May 2020
AS is an Equal Opportunity employer. As part of our commitment to equality, diversity and inclusion and promoting equality in careers in science, we hold an Athena SWAN Bronze Award and have an active Equality, Diversity and Inclusion programme of activity. We welcome applications from all sections of the community. People from ethnic minorities and disabled people are currently under-represented and their applications are particularly welcome. We operate a guaranteed interview scheme for disabled candidates who meet the minimum criteria for the job. We are open to a range of flexible working options, including job sharing, to support childcare and other caring responsibilities.
Skills are listed as either Essential or Desirable. Desirable skills importance rating in parenthesis (1 is high, 5 is low)
Communication skills - a) oral skills b) written skills
- Fluent in written and spoken English language - Essential
- Being able to present results and ideas clearly to colleagues - Desirable 
Computer / IT skills
- Excellent computer programming skills. Experience with Python, Git, & Machine Learning packages - Essential
- Needs to be able to manage their own workflow, based on their findings. - Essential
- To work as part of a team, but also work independently. - Essential
- Strong skills in mathematics and statistics - Essential
- A PhD in a quantitative subject (or equivalent) - Essential
- Completed course(s) /qualification in machine learning - Desirable 
Skills / Experience
- Experience with data processing and analysis, and writing efficient code - Essential
- A good understanding and keen interest in environmental sciences. - Desirable 
You can apply for this job online or you can print off the application forms, fill them out by hand and mail them.
Apply by post:
If you would like to apply for this job but cannot apply online, you can print the application form(s) and post it back to us.
Please ensure you complete all required sections of the application form(s) and include a Cover Letter and a copy of your CV.
When posting your application, ensure there is sufficient postage.
- Send your completed application forms to:
- Human Resources Team
British Antarctic Survey
High Cross, Madingley Road
If you need more information
- Email: [email protected]
- Telephone: +44 (0)1223 221400
- Facsimile: +44 (0)1223 362616
The information you provide during the application process will only be used for the purpose of progressing your application, to fulfil legal or regulatory requirements where necessary or, in the case of the Equal Opportunities Monitoring Questionnaire, to help BAS meet its equal opportunities policy.
The British Antarctic Survey will not share the information you provide with any third parties, and the information will be held securely by the British Antarctic Survey whether the information is in electronic or physical format. Please note that the Equal Opportunities Monitoring Questionnaire will be detached from your application prior to the short-listing of candidates for interview.
Unsuccessful applications will be securely destroyed 6 months after the end of the recruitment process (or 1 year after the end of the recruitment process in the case of Marine Staff and AEP. The applications of successful applicants will be retained as part of their personnel file.
Further information can be found in the information notice of NERC, our parent body.