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of statistical analyses and modelling. Experience in handling and analyzing large datasets. Experience in employing high performance and cloud computing services. Knowledge in GIS. Knowledge on obtaining
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. Experience with Linux/Unix environments, cloud computing, and version control systems (e.g., Git). Additional Information: Responsibilities: Perform comprehensive analyses of microbiome sequencing data (e.g
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learning applied to geospatial data Experience with Amazon Web Services or other cloud-based computing platforms Special Instructions to Applicants: For full consideration, applications must be submitted
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terrain dynamics. Familiarity with cloud computing platforms (e.g., AWS, Azure) and advanced analytics. Knowledge of causal inference or complex systems theory is a plus. To Apply: Any questions can be
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model APIs, cloud computing environments, and R for additional statistical analysis. For decision support prototype development and evaluation, web-based user interface design, human-computer interaction
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to work at the forefront of environmental remote sensing, leveraging unique datasets and advanced computational methods to address critical questions in land change science and fire ecology. The position is
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skills. Ideal applicants will also have experience with some combination of: a) Machine learning e) code optimization and software delivery f) big data visualization g) cloud computing h) web application
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intersection of climate, agriculture, and natural resources management Prior work assimilating satellite imagery data into models Experience with the Linux operating system, high-performance computing, cloud
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Posted on Wed, 02/12/2025 - 13:31 Important Info Deprecated / Faculty Sponsor (Last, First Name): Han, Summer Stanford Departments and Centers: Medicine, Biomedical Informatics Research (BMIR