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in Python or R. Python preferred. Knowledge of sensor placement and instrumentation, especially for water systems (e.g., pressure, flow, or water quality sensors). Knowledge of open-source water system
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audiences. We’re looking for someone who: Can apply data science to real-world problems. Is comfortable with Python, R, SQL, or similar tools for analysis and modeling. Can translate messy datasets
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, or related discipline). Degree must have been received within the past five years. Preferred skills: Experience with ecological modeling, spatial analysis and statistics, ArcGIS Pro software, Python
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in agricultural soil microbiology. The participant will also have active exposure to statistical data analytics using R, Python, and current bioinformatic software. The participant will gain or enhance
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have been received within the past five years. Preferred skills: Experience with ecological modeling, spatial analysis and statistics, ArcGIS Pro software, Python and R coding. Stipend $60,000.00
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development pertaining to chemical and biological detection. You will gain experience with algorithms, data analysis, Deep Learning, Python, pytorch and /or tensorflow, NLP, genetic algorithm, computer vision
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data as well as experience with data analysis software like Excel, Python, and Matlab. Application Requirements A complete application consists of: Zintellect Profile Educational and Employment History
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. Analyze large-scale data and summarize findings using statistical software (SAS, Python, R, and/or similar programs). Collaborate with team to improve standardization, utility, and public health potential
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of their service lives), statistics, emerging data science tools and techniques A demonstrated ability to use a statistical programming language such as R or Python for non-linear data fitting, and optimization
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setups Familiarity with micro/nanofabrication or clean room techniques Experience in or willing to learn COMSOL, Matlab or Python is preferred Mentorship and Training Opportunities: Work with PIs to create