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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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—typically developed in Unity—to offload compute-intensive tasks dynamically across a distributed infrastructure. A critical part of this effort will involve integrating and exposing hardware accelerators
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developed in discussion with the recruited candidate and the team, the main question of the project is the extent to which alterations to chromatin distribution and methylation arise, and how they contribute
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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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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