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The position is placed at the Division of Astrophysics in the Department of Physics to work with David Hobbs on developing algorithms to improve the quality and scientific information that can be
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-of-the-art semantic and instance segmentation algorithms for 3D and 4D microtomography data. The project has a particular focus towards analysing fibre-based materials but will also consider other material
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environment project, we will develop automated species and community recognition, particularly focusing on pathogenic soil fungi, with help of deep-learning algorithms fed with microscopic image and Raman
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algorithms. Work duties The main duties involved in a post-doctoral position is to conduct research. Teaching may also be included, but up to no more than 20% of working hours. The position includes
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cost-efficiency in supply chains; centralised versus decentralised storage and distribution; and short-term food security needs versus long-term circularity and environmental goals. This shift is vital
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-temporal analysis, use of latent variable models such as VAEs, GANs, and diffusion models to capture complex distributions, methods for interpretability (e.g., SHAP values), as well as uncertainty
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experiments to evaluate protein self-assembly. An ability to derive equations and writing code to analyze data on protein self-assembly. Practical experience in measuring protein size distributions and