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backgrounds. The Faculty external link has six departments: Biology, Pharmaceutical Sciences, Information & Computing Sciences, Physics, Chemistry and Mathematics. Together, we external link work on excellent
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going to do Analyze a uniquely extensive neuroimaging dataset (90 minutes of functional MRI per participant across multiple sessions and conditions, detailed structural and diffusion-weighted data
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Organisation Job description A 2-year postdoc position in computational social choice for digital democracy is available at the Bernoulli Institute for Mathematics, Computer Science and Artificial
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. The key methodological tools for these studies are digital ethnography and conventional primary data collection (surveys, interviews). The post is part of two Horizon Europe projects: INSPIRE and EQUICARES
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appointed at the Computer Science Department of the Institute for Computing and Information Sciences (iCIS ). Radboud University’s iCIS is an internationally recognised institute, consistently ranked among
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uncovering companion biomarkers for precision treatment using cutting-edge bioinformatics and proteomics approaches. You will analyze bulk and clonal protein expression data from large melanoma cohorts
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science, environmental economics, social sciences, or related fields). Demonstrated expertise in planetary health or related areas, with a track record of high-quality research outputs. Proven experience in
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perspective in close cooperation with the Dutch Poisons Information Centre at the University Medical Centre Utrecht. We are also committed to sharing science and collaborate with other research groups in
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of the Institute of Cultural Anthropology & Development Sociology Co-organise and participate in academic and public events related to the project Where you will work The Faculty of Social and Behavioural Sciences
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progress by streamlining research across disciplines. In chemistry, it enables the modeling of complex structure-function relationships with unprecedented accuracy. Additionally, deep generative models allow