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funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Are you interested developing new machine learning methods for precision medicine and
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consequences of keel bone deviations: What impact do these have on hen behaviour and wellbeing? high-tech welfare assessment: Help develop a non-invasive computer vision method to track and analyze how hens move
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rotation forestry towards continuous cover forestry methods is debated in Scandinavia as a way forward to increase biodiversity and climate resilience. This postdoc project will be based on empirical field
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develops an adaptive AI-guided XR platform for capturing and transferring expert manufacturing knowledge. Your focus will be on developing AI methods for analyzing and modeling human workflows based on data
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and written. Solid skills in computer programming (Python / Matlab). Experience with CAD and CAE tools. Knowledge of computational fluid dynamics (CFD). Knowledge of finite element method (FEM
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This position creates an inclusive environment to closely work with the Swedish industry in developing methods and tools related to flow-induced acoustics, which is a critical aspect for modern
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most rapidly in the boreal region, will require adaptive management strategies. For this purpose, a transformation from traditional rotation forestry towards continuous cover forestry methods is debated
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: Help develop a non-invasive computer vision method to track and analyze how hens move in 3D space. You will gain hands-on experience in behavioural studies, animal welfare science, and innovative data
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samples (blood, serum, feces, urine, saliva etc.) experience with Anova knowledge of registers at ABIS, as well as other national registers good computer skills, including knowledge of SPSS and Exel
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novel machine learning method development. However, you will be part of a larger cross-disciplinary research initiative involving both computer and material scientists, providing excellent opportunities