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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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or glia) Experience with microglia biology or neuroimmune interactions Behavioral experiments Solid data analysis skills (e.g., MATLAB or Python for calcium imaging data) FELASA B certification to
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collaborative in nature. A strong publication record in reputable peer-reviewed journals is highly desirable. Proficiency in programming, particularly in R, Python, or other relevant languages, is
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in Python programming for geospatial data processing, modeling, and mining. Publications in high-quality international peer-reviewed journals within a relevant field, especially experience in
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this project, we seek candidates with the following expertise: Documented experience in analyzing genomics, epigenomics, and/or transcriptomics datasets using R, Python, and shell. Experience in
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programming environments, especially R or Python; the applicant’s ideas concerning how the OCCPOL data could be developed and used; and motivation to participate actively in a collaborative research project and