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sciences Strong background in deep learning, with experience in probabilistic models (e.g., Variational Autoencoders, Bayesian approaches) Proficient Python programming for machine learning and scientific
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for physical AI systems that learn and adapt through continuous exposure to multimodal sensory and radio data, and acts upon real-world environment through distributed coordination and control. Emphasis will be
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The Department of Ecoscience at Aarhus University invites applications for two postdoctoral positions to strengthen our research on image recognition, computer vision and deep learning applied
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. Strong skills in geospatial analysis. Strong skills in image analysis and machine learning. Proficiency in scientific programming and data analysis using tools such as Python, R, MATLAB, or similar
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analysis and biomedical data analysis, with demonstrated experience in organ segmentation from medical images, using both traditional and machine learning–based methods, and creation of large segmentation
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, Bash). Experience working in a Unix/Linux environment, including setting up and managing High Performance Computing (HPC) clusters. Familiarity with metagenomic data analysis and machine learning
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geoscientific applications. Current research includes large-scale crop mapping, wetland monitoring, and the integration of machine learning with remote sensing and geophysical data for groundwater mapping. Your
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hold a PhD in oceanography, marine ecology, computer sciences, data sciences or similar. We expect that you have: Expert knowledge on network modelling, especially aimed at ecological applications Strong