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Field
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advanced data analysis. Most of the research will be carried out in the battery research laboratories, which are equipped with state-of-the-art facilities for materials synthesis, characterization (XPS
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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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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 omics, image analysis, and computational analysis of complex biological data. Work duties The main duties involved in a post-doctoral position is to conduct research. Teaching may also be included
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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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), statistical analysis of LHC data or beyond-the-Standard-Model phenomenology, is meriting. Experience with large-scale training on GPU and HPC systems, with design of experiments and active learning, with open
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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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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