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outputs. Proficiency in scientific programming and computational tools commonly used in numerical modeling and environmental data analysis, such as Python, MATLAB, Fortran, C/C++, or comparable languages
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National Aeronautics and Space Administration (NASA) | Greenbelt, Maryland | United States | 19 days ago
languages like Python. The group currently leads development of spaceflight readout electronics for the Probe Far-Infrared Mission for Astrophysics (PRIMA) and the balloon-borne EXperiment for Cryogenic Large
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relevant research areas Proficiency in Python programming Excellent written and verbal communication skills in English Writing scientific papers and exploring new technologies. Application and Selection
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/ Deep Learning Knowledge of: Active learning, Bayesian optimization Reinforcement learning or decision-making systems Experience with: Python ecosystem (PyTorch, Scikit-learn) Data pipelines and
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, natural language processing, medical text mining, or clinical AI. Strong programming skills in Python and/or R. Familiarity with medical terminology, ICD codes, phenotype extraction, or HPO. Ability to work
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cooperatively with others. Preferred Qualifications: • Proficiency in handling remotely sensed geospatial datasets and programming languages, particularly R or Python. • Knowledge, experience, and
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including statistical programming (e.g., STATA, RStudio, Python). You will demonstrate previous experience of contributing to publications/presentations as well as the ability to manage your own academic
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data. Statistical analysis using R and/or Python. Reproducible computational workflows. Scientific writing and publication. Microbiome research and host-associated microbial communities. The ideal
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. Candidates must be supportive of the mission of the Land-Grant system. Candidates must also have a commitment to UF core values . Preferred: Experience with R/Python programing languages is desirable. Special
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development, spin simulations, or MR signal modeling is highly desirable. Strong programming skills, for example in Python, MATLAB, C/C++, or a comparable scientific computing environment. Experience with