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collection has been the focus of concentrated digitisation efforts during the past eight years, including specimen photography. This new project seeks to harness this dataset using machine learning in order to
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; Demonstrated interest in research on the intersection of society and AI, preferably as it relates to forms of algorithmic bias; Experience with machine learning or computational modeling; Strong quantitative
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bioinformatics and proteomics approaches. You will analyze bulk and clonal protein expression data from large melanoma cohorts, integrate molecular, histological, and clinical data through machine learning (ML)/AI
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analyzing textual and visual content with supervised machine learning. Conducting focus groups with social media users to understand how this content may shape beliefs and attitudes about AOMs, a healthy diet
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PhD degree in either machine learning or computational molecular sciences. Advanced knowledge in molecular machine learning. Advanced knowledge in computational chemistry. Advanced programming skills
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Employment 0.8 - 1.0 FTE Gross monthly salary € 3,378 - € 5,331 Required background PhD Organizational unit Faculty of Science Application deadline 20 August 2025 Apply now Do you want to conduct
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sciences, or a related field. You have a strong background in quantitative research methods, including statistical modelling, data analysis, machine learning, and/or GIS analysis. You have proven expertise
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for the analysis and integration of –omics data. The group has a strong track record in (integrative) computational omics analysis, algorithm development, machine learning and scientific data infrastructure