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-Chem • You will be contributing to the development of machine learning models used on data from Poleno Jupiters, applying Python and machine learning. • The position will focus on implementing
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Background in machine learning or deep learning methods, including Graph Neural Network (GNN) Experience with Large Language Models (LLMs) applied to biological data collection, extraction, and standardization
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statistics, AI and machine learning methods, including demonstrated experience in analysing multiple global change drivers, e.g. land use intensity, climate change, nitrogen deposition. Proven capability
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of bioacoustic signals. Extensive experience with programming (Matlab, R, Python) including GPU programming is required, and familiarity with edge-based machine learning (particularly sound event detection), open
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, especially but not exclusively related to AI, https://digitalcurriculum.au.dk in collaboration with colleagues from CED and NAT Join as a co-teacher in a few of the departments’ workshops and teaching
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data integration and analysis Integrate phylogenomic and functional data using machine-learning approaches for candidate gene prioritisation Contribute to software and web-tool development Present
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of Civil and Architectural Engineering Theme 9: Building the resilient, flexible, multi-energy microgrids of tomorrow hosted by the Department of Electrical and Computer Engineering Theme 10: Advanced
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such as Google Earth Engine statistical modelling, machine learning, cloud/high-performance computing retrieving ecologically relevant environmental data from national to global databases research and/or