A three year training programme to develop your research in a number of directions including data visualisation, research software development, and applications of HPC, cloud computing and machine learning.
We are seeking an enthusiastic and innovative data scientist to join a research team that uses national datasets and data science methods to develop approaches to understand and model the impacts of environmental change on biodiversity, ecosystems and the services they provide. You will work on existing projects and develop your own areas of applied research in collaboration with a broad range of scientists within UKCEH and externally.
You will join the Biodiversity Monitoring and Analysis team at the Biological Records Centre where you will have a key role in the DECIDE and AgLand projects.
DECIDE seeks to:
- Improve existing biodiversity information through near real-time, fine resolution (<1km), species distribution modelling, by combining citizen science records with large-scale environmental sensor data, including earth observation land cover data.
- Enhance biodiversity citizen science through adaptive sampling, by using intelligent digital engagements so that they re-deploy a portion of their effort to the times and places where records will optimally improve the model outputs.
- Make biodiversity information more accessible and useful to end users through data flows and co-design of automated data communication with local and national public bodies and business.
- The aim of AgLand is to provide new data and models to support decision makers in the design and management of future agricultural landscapes. These will deliver both sustainable food production, and a wide range of other ecosystem goods and services. Your role will be supporting the data science needs of this project.
- You will join a team of scientists including modellers, social scientists, visualisation experts, and agronomists to help deliver these ambitious projects.
- You will join a research team based at UKCEH Wallingford, but remote working will be considered for the right candidate.
Over the 3 years you will gain skills in:
- The use of High Performance Computing
- Research Software Engineering
- R programming
- Data visualisation
- Use and development of APIs
- Project Management
Knowledge & Qualifications
- A PhD, or equivalent level of experience, in quantitative research (in the environment and ecology, or other areas of science with transferable quantitative skills e.g. Data science, Computer science, Physics, etc.)
- Expertise in the R programming language
- Some familiarity with biological recording in the UK, and a keen interest in the natural environment
Experience/Proven abilities related to the position
- Proven ability to learn quickly
- Experience in reproducible methods including R Notebooks and Git/GitHub
- Ability to innovate, applying novel methods/technologies to existing problems
- Team working experience, particularly in a collaborative coding context
- R - Experienced writing reproducible code (examples could include: functions, packages & R markdown documents)
- Data visualisation
- Working with large datasets/models
- Good time management skills across multiple projects
- Excellent communication skills, to a range of audiences
- Able to build analysis workflows/pipelines from well-defined analytical steps
Core Behaviours & Values
- You will demonstrate a commitment to promote and adhere to UKCEH values of Excellence, Integrity and Teamwork.
What we offer
Find out the benefits of working with UKCEH
How to Apply
To apply for this position, click the link. As well as a CV, please provide a covering letter detailing why you may be suitable for the role.
We value your feedback on the quality of our adverts.
If you have a comment to make about the overall quality of this advert,
or its categorisation then please