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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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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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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
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education and/or experience in one or more of the following: Experience with FPGAs, Microelectronics, Machine Learning, and/or Software Development using languages like C/C++, Java, and Python Application
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using Python and MATLAB. Why should I apply? Under the guidance of a mentor, you will engage in a variety of research activities, including: developing machine learning algorithms for various research
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, python and GitHub Strong background in and knowledge of remote sensing with a variety of data sources Experience with USDA Forest Service Forest Inventory and Analysis (FIA) data Experience with geospatial
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such as Python or Matlab. Taken a course in statistics. Application Requirements A complete application consists of: Zintellect Profile Educational and Employment History Essay Questions (goals
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a demonstrated ability to use a statistical programming language such as R or Python. Domain knowledge demonstrated by a degree in economics, data science, statistics, forestry, natural resources