Research Associate in Machine Learning for Pollinator Behaviour Analysis

We have an exciting role working with collaborators in Sheffield and at Ohio State University that combines ecology, machine learning, hardware and software development to solve a critical challenge in understanding the impact of pesticides on bumblebees. We are seeking a highly motivated Post-Doctoral Research Associate (PDRA) who wants to apply their background in engineering/science to develop a novel and impactful approach to record and detect subtle changes in bee behaviour. The work will include deploying mathematical tools, such as Bayesian inference, onto hardware to allow real-time 3D tracking of bumblebees. You will therefore need to be comfortable with engineering mathematics (linear algebra, probability, calculus) and have some experience writing software. You will also need to have prior experience of submitting work to high-impact peer-reviewed journals and conferences.

You will be working as part of a friendly and supportive team (including PhDs, research software engineers, ecologists and other experts). You will be based in Sheffield but will be visiting Ohio State University to support the team there (helping with training and deployment). The Sheffield machine learning group, and wider computer science department are both quickly growing, and have a history of collaborations across disciplines to solve important challenges.

Together, we will use the system to explore both the mechanisms through which pesticides affect pollinators and the agricultural implications of the behavioural changes. The outcome of the project will be a sensitive method for detecting treatment induced behavioural change in bumblebees, and evidence regarding the effect of treating plants with fungicides on the foraging behaviour of bumblebees. You will lead the preparation of publications and presentations: allowing us to support the wider community in deploying this method. This BBSRC funded project is also likely to lead to many related studies – both at Sheffield and beyond. The wide range of disciplines involved means that you will have a great opportunity to move into several future areas (machine learning, ecology, computer vision, etc).

We are committed to exploring flexible working opportunities which benefit the individual and University.

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