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. The researcher will primarily design and execute total X-ray and neutron scattering experiments, using pair distribution function (PDF) analysis to elucidate the short- and medium-range atomic order in disordered
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proteomics, advanced image analysis, and computational approaches to investigate molecular and cellular heterogeneity and to integrate spatial molecular information with histopathological and clinical data. We
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cells, and their spatial organization within the tumor microenvironment. We use spatial transcriptomics and spatial proteomics, advanced image analysis, and computational approaches to investigate
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collection with informal caregivers, healthcare professionals and other stakeholders, register and retrieve data from REDCap. Analyse qualitative data using, for example, reflexive thematic analysis
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spatial transcriptomic data. A demonstrated interest in data visualization and large-scale data analysis is highly desirable. The ideal candidate will have a keen interest in understanding complex
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data analysis and machine learning (e.g. XGBoost), including model interpretation techniques (e.g. SHAP). Very good oral and written proficiency in English. Excellent communication skills, ability
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record in relevant peer-reviewed journals, including publications demonstrating a substantial individual contribution. Experience with scientific programming, experimental automation, and data analysis
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. Experience with scientific programming, experimental automation, and data analysis using, for example, Python, MATLAB, or LabVIEW. Experience with numerical modelling of nonlinear or integrated photonic
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research environments in Computational Science, the research and education has a unique breadth, with large activities in areas such as numerical analysis, mathematical modelling, development and analysis
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strong scientific background with relevant expertise in cell and/or molecular biology. Interest in programming, computational biology and statistic towards high-throughput data analysis is considered a