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career stage. Experience with High-Performance Computing (HPC) clusters, geospatial foundation models, large-scale geospatial processing or cloud-based Earth Observation platforms would be advantageous
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applications (experience in R and/or Python, as well as cloud computing) A strong background in statistics and biology Experience managing and curating large datasets Excellent oral and written
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, or cardiometabolic disease Track record of peer-reviewed publications relative to career stage Experience with multi-omic data integration Familiarity with HPC or cloud computing environments Why
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with: Experience with web-GIS development or geospatial data visualization. Experience with high-performance computing clusters or cloud-based Earth observation platforms (e.g., GEE Python API
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Computing , Health Science , Life Science Job Type Postdoctoral Employment - Hours Full time Duration Fixed term Qualification PhD Sector Academia Apply on website (This will open in a new window from
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mentor to other members of the community. KNOWLEDGE, SKILLS, AND ABILITIES REQUIRED: Background in machine learning Background in cancer biology Experience with R and/or Python Experience with cloud
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computational biology and its common applications (experience in R and/or Python, as well as cloud computing) A strong background in statistics and biology Experience managing and curating large datasets
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experience in computational biology and its common applications (experience in R and/or Python, as well as cloud computing) A strong background in statistics and biology Experience managing and curating large
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employing statistical estimation techniques. Experience with high-performance computing. Experience with geospatial data processing and Geographic Information Systems (GIS) tools. Eligibility for immediate