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to help you settle in. Discover more Find more general information about doctoral studies at Chalmers here . Application procedure The application should be written in English be attached as PDF-files, as
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Description: Broadleafification, i.e. the process of increasing the share of broadleaf tree species within conifer-dominated forests, is a promising strategy for biodiversity conservation in managed (hemi
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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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://www.slu.se/en/about-slu/work-at-slu/ Benefit of Broadleaves on Bats, Birds and Beetles Research subject Biology Description: Broadleafification, i.e. the process of increasing the share of broadleaf tree
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among qualified applicants based on their qualifications and their ability to benefit from studies at the doctoral level. After the selection of the suitable candidate, the process for the admission
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employment benefits at Linköping University is available here. Union representatives Information about union representatives, see Help for applicants . Application procedure Apply for the position by clicking
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selection will be made among qualified applicants based on their qualifications and their ability to benefit from studies at the doctoral level. After the selection of the suitable candidate, the process for
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the Division for Computer network and systems and the employment is placed with Chalmers University of Technology. Our research spans from theoretical computer science to applied systems development. We provide
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representatives, see Help for applicants . Application procedure Apply for the position by clicking the “Apply” button below. Your application must reach Linköping University no later than 24th of September 2025
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with expertise in materials characterisation, computer vision, computational modelling, and machine learning. The other PhD positions connected to the project are: PhD Student Position in Generative