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learning, for offshore industrial produced water treatment processes. The developed methods/solutions should be tested and demonstrated on a globally leading pilot-plant sited at Aalborg University
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close collaboration with a specific group (DARSA) specialized in developing and applying remote-sensing tools and innovative open-source machine-learning methods. Key responsibilities Develop effective
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design platforms for rapid deisgn and optimisation of novel targeting modules. Your responsibilities will include: Designing and implementing state-of-the-art deep learning architectures for protein
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experimental and suited for candidates who enjoy hands-on research, learning new techniques, and working across disciplinary boundaries. Your competencies We seek a highly motivated candidate with a strong
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its BSc and MSc programs, which are based on AAU's problem-based learning model. The department leverages its unique research infrastructure and lab facilities to conduct world-leading fundamental and
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sedimentary archives, to facilitate and use in-situ and remote sensing observations of polar environments, and to acquire skills within VibroSeismic data acquisition, analysis and interpretation. The position
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has more than 600 students in its BSc and MSc programs, which are based on AAU's problem-based learning model. The department leverages its unique research infrastructure and lab facilities to conduct
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leading academic and industry partners within the Horizion Europe Project. Your profile We are looking for a highly motivated and talented candidate with a background in deep learning. The required
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imaging, deep proteomics, metabolomics, metaproteomics, and machine learning (ML) approaches to develop diagnostic classifiers, spatial tissue atlases, and identify potential therapeutic targets
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, demonstrating strong collaboration skills and the ability to acquire new skills and technologies. Prior expertise in architecture is not required. Outstanding spoken and written communication skills in English