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insights that inform biodiversity management. The project includes: · Apply of deep learning models to annotate bird and bat species from sound recordings. · Develop a Bayesian statistical
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more about our benefits and what it is like to work at SLU at https://www.slu.se/en/about-slu/work-at-slu/ Development of statistical methods for estimating plant population size and change Mathematical
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that support the unit for area protection and marine spatial planning, as well as operations at SLU Aqua. Your profile You have documented expertise in marine ecology and computer vision and machine learning
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) scientific studies Experience with relevant field data collection methods (e.g. chamber- or eddy covariance-based C flux measurements, biodiversity sampling methods) Computer programming skills (e.g. Matlab, R