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in and motivation for genomics or/and biodiversity conservation studies. Strong background in AI/ML fundamentals and extensive experience with deep learning (DL) methods. Demonstrated proficiency in
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candidate would be a PhD in geophysical sciences, computer science, or machine learning with experience in developing and verifying deep learning-based models for large dynamical systems (e.g. weather
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(particularly Deep Learning), will also make it possible to leverage the collected data to enrich knowledge of ovine behavior. The candidate will join a dynamic research group within the Image/Vision team
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. Demonstrated experience in either of the following areas (a) data science, (b) theoretical nuclear reaction models and/or (c) deep learning-based machine learning and applications of artificial intelligence
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Join us at the Department of Electrical and Computer Engineering at Aarhus University for a postdoctoral position focused on deep learning based analysis of remote sensing data for groundwater
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techniques and genomic data analysis. Background in and motivation for genomics or/and biodiversity conservation studies. Strong background in AI/ML fundamentals and extensive experience with deep learning (DL
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-of-the-art methods, datasets, and challenges Proven experience with: Video data processing for learning and inference Deep learning architectures for video analysis Python programming and PyTorch framework
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expertise in deep learning and representation learning applied to biological data, experience with large-scale multi-omics datasets (such as single-cell and proteomics), and strong programming skills in
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implement state-of-the-art data science principles into dental practice. While our primary focus is on the use of deep learning in (dental) imaging, our work expands into any type of data (e.g. tabular data
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of the following areas: Wireless and satellite communications AI/ML for dynamic networks including Graph Neural Networks, Transfer Learning, Deep Reinforcement Learning, and Transformer-based models