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of complex brain processes. The prospective PhD candidate collects brain MSI data and develops novel machine learning methods in connection to generative models such as flow matching. Therefore, the doctoral
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on innovative development and application of novel data-driven methods relying on machine learning, artificial intelligence, or other computational techniques. The specific focus is on development and
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methods relying on machine learning, artificial intelligence, or other computational techniques. The specific subject area is focused on the ecological and evolutionary processes generating and shaping
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). The project focuses on developing computational models for cancer risk assessment, integrating multiple types of data and risk factors. The main objective is to design and apply machine learning and deep
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information about us, please visit: www.dbb.su.se . Project description The candidate will develop machine learning (ML) strategies, primarily revolving around interpretable ML and generative AI, to study
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part of SciLifeLab BioImage Informatics Facility (BIIF) as described below. The Vi3-Division gathers a unique combination of expertise in computerized image processing, human computer interaction, and
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at Sahlgrenska Academy of relevance include genomics, metagenomics, culturomics, proteomics, transcriptomics, software development, machine learning, and other statistical analyses of large-scale health data
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Extensive knowledge of relevant machine learning and AI techniques Self-motivated individual with ability to work independently Teaching and mentorship abilities or interests in personal development A