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Field
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research prototypes to real-world deployment environments, including cloud, secure enclaves, trusted research environments, and leadership computing platforms. Candidates should be comfortable working in a
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computing and/or cloud computing; familiarity with Earth system models through model development, model execution, and/or model performance diagnoses; applied mathematics methods such as machine learning
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in internal meetings and at national/international conferences. ● Collaborate with an interdisciplinary team (bio)statisticians, data scientists, computer scientists, and climate scientists
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with PyTorch, required to have experience developing code with a team through collaborative version control Experience working with large datasets and cloud computing environments. Solid background in
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and funding availability. VISION Position Purdue as a national leader in AI-driven software and systems research spanning edge computing, cloud and distributed systems, high-performance computing (HPC
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, and familiarity with computing in the cloud/on HPC Strong data visualization and communication skills for technical and non-technical audiences Experience with interdisciplinary or collaborative
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analytics projects as needed (e.g., ticketing, fan engagement, and scheduling). Build and maintain data pipelines and models using R, Python, SQL, and cloud computing resources, following best practices
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, and familiarity with computing in the cloud/on HPC Strong data visualization and communication skills for technical and non-technical audiences Experience with interdisciplinary or collaborative
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. For applicants to the Microbial Bioinformatics track: PhD or equivalent in Computational Biology, Microbiology, or a related field. At least one published contribution in computational biology, microbiology, or a
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version control ● Experience working with large datasets and cloud computing environments. ● Solid background in statistical modeling and inference ● Excellent written and oral communication skills, with a