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organizational skills. Experience with using machine learning packages (e.g.PyTorch). Completed academic courses in AI or machine learning. Interest in societal, ethical and philosophical questions. We consider it
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sizes and frequencies by: Measuring rock fractures from UAV data using manual and automated mapping approaches (e.g., machine learning, convolutional neural networks). Monitoring physical weathering
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machine learning packages (e.g.PyTorch). Completed academic courses in AI or machine learning. Interest in societal, ethical and philosophical questions. We consider it an advantage if you bring one or more
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, Introduction to Python, making figures using GGplot2 and basic machine learning. These courses are offered to PhD candidates through the PhD Course Centre of the Graduate School of Life Sciences . In
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bringing together a diverse team of PhD candidates who will focus on three key areas: Probabilistic and differentiable algorithms for machine learning; Programming language implementation for high
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- and machine-learning-based methods that automatically describe and model geodata sources using textual metadata (NLP) and the geodata itself; contribute to a corpus of geo-analytical scenarios with
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transport proteins in lipid membranes. Furthermore, the ultimate long-term goal is to integrate these cells in a dialysis machines. The objectives for this position are to: Formulate synthetic cells with
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to develop synthetic cells that mimic tubular function by integrating transport proteins in lipid membranes. Furthermore, the ultimate long-term goal is to integrate these cells in a dialysis machines. The
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, including abstract geospatial workflows; design AI- and machine-learning-based methods that automatically describe and model geodata sources using textual metadata (NLP) and the geodata itself; contribute