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description The postdoctoral project is focused on development and the exploitation of machine learning tools to accelerate the analysis of microtomography data at the MAXIV synchrotron facility. MAXIV
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learning. The employment is full-time for two years starting from August 1st 2025 or by agreement. Apply latest April 7th 2025. Project description Geometric deep learning refers to the study of machine
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. The group studies the behavioral, neural, and computational principles behind human learning and decision-making in social environments. Our interdisciplinary approach combines behavioral experiments
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the opportunity to develop your own research ideas within the lab’s focus areas Build and refine computational models of human innovation and learning processes Design and test AI algorithms
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The postdoc fellow will conduct research in the intersection of AI/Machine Learning and Software Technology. The advertised position will be placed in the DISTA research group (https://lnu.se/en/dista
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proposal that will be further developed and contextualized in collaboration with the research leader in the research environment. Your research topic needs to be relevant for student learning in higher
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bioinformatics methods have made significant strides, AI approaches - particularly deep learning - are revealing patterns and relationships in biological data that were previously inaccessible. As a postdoctoral
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to solving applied problems through research, collaboration and education on sustainable plant production. We teach and research plants for food, feed and energy. The research and teaching focus
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The Rantalainen group is focused on application of machine learning and AI for development and validation of predictive models for cancer precision medicine, with a particular focus computational pathology. Our
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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