The Alan Turing Institute, the UK’s national institute for AI and Data Science, is seeking a Research Associate to join a newly funded research project to explore the environmental drivers of Antarctic sea ice as part of a national and international collaboration.
The pst holder will join the Turing’s Data Science for Science and Humantities programme and work alongside researchers from all disciplines across the Turing’s university partner network, and with national research facilities, to make effective use of state of the art methods in artificial intelligence and data science.
The programme is looking to recruit a Research Associate (RA) to develop new machine learning/deep learning/computer vision methods to monitor and predict sea ice change around Antarctica using synthetic-aperture radar (SAR) imagery and other observational data from satellite and surface sensors, as part of an international collaboration. More specifically, the RA will work as part of a cross-institute team to build upon our seasonal sea ice forecasting framework, IceNet, by integrating additional (including SAR) data.
The candidate will work within Turing’s Environment and Sustainability research theme, which seeks to develop methods to provide the meaningful insight to inform decision-making, improve risk management and enhance our resilience to climate change will require working across disciplines, bringing together methodology and expertise from different fields to develop tools and computational frameworks that can integrate data from multiple sources, available at different spatial and temporal resolutions and with different biases and uncertainties.
The RA will play an active part in all aspects of research from data preparation, to the development of research questions, modelling and analysis, and writing up/publication. Technical meetings will take place between the partner institutions, establishing a robust platform for developing future programmes between environmental science researchers, The Alan Turing Institute and the wider scientific community. This is a collaborative research role and so it is crucial that you enjoy working with others, and are responsive within an interdisciplinary research environment.
We are looking for experience in one or more of the following areas: deep learning; computer vision; statistical machine learning; modern statistical programming languages including probabilistic programming; applying the principles of reproducible data science.
Applications are welcome from a wide range of disciplinary backgrounds, including the physical sciences, computer science, statistics, or mathematics, and particularly from candidates whose prior research has a strong computational focus.
The postholder will be line managed by Dr Scott Hosking, Senior Research Fellow, and will work closely with other environmental researchers at the Turing, as well as collaborators at the British Antarctic Survey (BAS) and University of Leeds.