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Field
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physiology, forestry, geography) Background in data intensive processing and analysis using open-source code (e.g., Python, R) Demonstrated proficiency in code documentation and reproducibility, and
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experiments using tools such as cell imaging, CRISPR, chemoproteomics, protein purification or structural biology are required. Desired Qualifications* Programming skills in Python or R are desired. Modes
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Python Experience developing, testing, and refining machine learning models Experience developing HPC workflows Excellent written and oral communication skills Ability to function as a teammate in a
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). Strong capability in data analysis, scripting, or laboratory automation (Python, MATLAB, or LabVIEW). PhD must have been obtained within 3 years from date of hire. Preferred Qualifications Extensive
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field Strong quantitative and statistical skills, with proficiency in R or Python Experience analyzing longitudinal, infectious disease, clinical, or high-dimensional data Demonstrated record of peer
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, defensible splits, and appropriate statistical analysis and interpretation of results. Strong programming skills in Python and proficiency with PyTorch or an equivalent framework. Strong organizational skills
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use of software such as R, Python, or similar analytical tools, are helpful. Exposure to modeling water or nutrient dynamics, studying low-water-requirement or salt-tolerant crops, or evaluating
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Python or similar by writing codes or using established software. Collaborate with colleagues on ML-assisted analysis of large multi-dimensional datasets. Collaborate well with other research teams and
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of multiple surveillance and administrative data sources. Development of reproducible analytical workflows using programming languages such as R and Python. Application of machine learning and predictive
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. Certificates/Credentials/Licenses Computer Skills Academic and research software relevant to job duties (Linux operating system, Gaussian/ORCA, AMBER/OpenMM, coding skills in Python). Supervisory