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Sentinel-1/2 time series. Strong proficiency in Python for geospatial data analysis and machine learning (e.g. XGBoost), including model interpretation techniques (e.g. SHAP). Very good oral and written
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, progression, and treatment response. This position focuses on the application and development of bioinformatics methods for the analysis of genomic cancer data, including large public international
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tumor initiation, progression, and treatment response. This position focuses on the application and development of bioinformatics methods for the analysis of genomic cancer data, including large public
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is very important that you who apply for this position have a great interest and knowledge in data analysis, filtering and modeling based on large amounts of data. It is important that you have a
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of multiple dataset) with a strong focus on single-cell RNA and ATAC sequencing and spatial transcriptomic data. A demonstrated interest in data visualization and large-scale data analysis is highly
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will lead sub-studies that map the functional nodes of the cerebellum with TIS and fMRI, from protocol development and individualised stimulation modelling to data collection, analysis and publication