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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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Postdoc in computational social choice for large-scale deliberation (1.0 FTE) (V25.0203) « Back to the overview Job description A 2-year postdoc position in computational social choice for digital
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’ sending and receiving regions. It uses big data and agent-based modelling to analyse the impact of those changing patterns of spatial mobility on EU regions and envisage policies to counterbalance
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a large interdisciplinary consortium of digital democracy researchers as well as several societal partners. The successful applicant is expected to carry out research on the algorithmic foundations
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bulk and clonal protein expression data from large melanoma cohorts, integrate molecular, histological, and clinical data through machine learning (ML)/AI-assisted methodologies. Your expertise in ML
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‘RobotLab’, large numbers of experiments can be carried out, yielding large datasets on properties of molecular systems. With this data, ML models are trained to predict the properties of molecular systems
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researcher will work as part of a team which also includes the principal investigator, two junior researchers writing PhD theses on ‘making’ in Roman literature, and two research assistants who support the
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delamination of TaC coating from the graphite substrate, which are mainly caused by the large thermal expansion mismatch between the coating and graphite substrate during chemical vapor deposition and during
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researchers writing PhD theses on ‘making’ in Roman literature, and two research assistants who support the team. Together, we work towards a new understanding of the ethics and aesthetics of making in
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interregional large scale transport infrastructure projects, such as the Lelylijn and the Nedersaksenlijn, which also aim to improve the interregional accessibility of rural areas. Moreover, we aim to include a