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postdoctoral researcher to join an interdisciplinary team developing deep learning models for antimicrobial resistance (AMR) detection directly from MALDI-TOF mass spectrometry data. The project is funded
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colleagues in the group and external partners in Denmark and abroad. You will work with the design and execution of research studies, the analysis and interpretation of data, and the dissemination of results
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colleagues in the group and external partners in Denmark and Europe. You will work with the design and execution of research studies, the analysis and interpretation of data, and the dissemination of results
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with an international team, establish experimental designs, and provide biological insight into the mechanisms of chromatin recognition and repair. The postdoc is expected to drive the project, including
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-Chem • You will be contributing to the development of machine learning models used on data from Poleno Jupiters, applying Python and machine learning. • The position will focus on implementing
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: Conceptualisation and synthesis of data integration and visualisation workflows. Data management and the development of knowledge graphs Development and application of AI and machine learning methods and pipelines
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and formalize relevant cognitive and behavioural mechanisms in computational models, including, where appropriate, learning, decision-making, belief updating, preference formation, habit formation
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Conducting evaluation and impact assessment of the Innovation Academy, including register-based analyses of innovation and entrepreneurship activities Developing and delivering courses and learning activities
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data or large data volumes in all information systems. We contribute methods and algorithms for machine learning, and data mining, including XAI, as well as for data access and query processing. Aarhus
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postdoctoral researcher to join the ICaRUS project at the section Automation and Control, Department of Electronic Systems, The Technical Faculty of IT and Design, Aalborg University. The position is full time