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Field
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, signal processing, and data mining A strong background in programming, statistical analysis, and spatial modelling and mapping Highly motivated to work on the subject and eager to work in an
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Proficiency: Proficiency in Geographic Information Systems (GIS) to map and analyze spatial determinants of urban health. Predictive Modeling Skills: Ability to develop predictive models and simulation tools
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climate sensitivity hazards such as power outage due to wildfire. Experiences or publications with methods such as quasi-experimental design, case crossover design and spatial statistics are all positive
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international collaborations Your profile at our group: analysis of high-throughput proteomic, (single cell) transcriptomic, digital spatial and other omics data in health and disease states multi omics data
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computer programming tools such as Matlab and/or Python. Knowledge of statistics and mathematical modeling. Experience in large spatial data processing, analysis, and interpretation. Experience in running
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participating in the collaborative development of: (1) spatially explicit baseline data of cropping practices, including identification of representative crop rotations, and (2) spatially explicit baseline
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, particularly single-cell RNA sequencing, spatial transcriptomics, and related approaches. Our research group uses single-cell genomics to study immunity at mucosal sites, with a focus on the lungs and
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time of employment, and the degree may be in sociology, psychology, political science, or related areas. Demonstrated knowledge of statistics and research experience of social surveys of an East Asian
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will be focused primarily on the development and application of novel computational algorithms to analyze and integrate diverse omics datasets, including single-cell RNA-seq, spatial transcriptomics and
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hydro-climate studies. Strong background with GIS tools and spatial analysis techniques. Demonstrated expertise in climate variability assessment and the use of climate models. Experience with