Can we use low-energy sensors and artificial intelligence to identify and count insects on an industrial scale? If this interests you, read on!
We are seeking an entomologist with experience of field survey techniques and insect identification, interested in working at the interface between computer science and zoology. The project is a collaboration with Nokia Bell Laboratories, Cambridge, a leading lab working in the areas of Future Devices, Mobile Sensing and Systems, Embedded Machine Learning, and Internet of Things research. You will join a team exploring the capability of emerging automated sensing systems and AI algorithms to scale up monitoring of insect abundance, biomass or diversity. You will be part of the Agroecology Group in the Department of Zoology and collaborate closely with faculty and students in the Departments of Computer Science and Technology and Plant Sciences.
You will also be part of the Cambridge Centre for Landscape Regeneration (CLR), https://www.clr.conservation.cam.ac.uk/ funded through the Natural Environment Research Council's Changing the Environment programme. CLR aims to provide the evidence needed to the UK government to fulfil its ambitions to bring back more nature to the British countryside and deliver more ecosystem services. The programme is focusing initially on two contrasting landscapes: the East Anglian fenland (primarily used for productive agriculture) and the Scottish Highlands (traditionally used for deer stalking and forestry plantations).
The project aims to design and implement an ultra-low power ML system on energy-autonomous devices (camera, microphone, and low-fidelity sensors) for biodiversity monitoring (especially insects). The project will leverage existing energy-autonomous devices, such as Nokia Bell Labs battery-less camera prototype.