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solutions. For more information about DHS visit: https://www.dhs.gov/mission. Project The DA-TC is seeking candidates who have the academic background to engage in the following projects. Projects will be
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improvements focused on vegetative effects on sediment transport. Data processing and analysis will be performed in the MATLAB, Python, Fortran, or R programming languages. Where will I be located? Location
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received a master's or doctoral degree in the one of the relevant fields Preferred skills: Experience/education in python, R, or other computer programing and statistics tools Education/experience in any
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modeling, quantitative analysis, and problem-solving within complex systems is highly valued. Candidates should have proficiency in relevant software tools and programming languages (such as Python, R
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have strong background in computer programming and exposure to one or more of the following skill sets are desirable: Python, R, materials optimization, design of experiments, materials structure
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engineering. Selection factors include coding proficiency / experience in: API and front-end development (eg. HTML, CSS, JavaScript); programming languages (e.g. PYTHON); relational databases and query
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experience with time-series data analysis and machine learning including reinforcement learning. Applicants should be proficient in Matlab and/or Python Point of Contact ARL-RAP Eligibility Requirements
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data acquisition for combustion diagnostics. • Familiarity with kinetic modeling and simulation of combustion processes (Cantera). • Ability to analyze and interpret complex experimental datasets (Python
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programming languages (including both MATLAB and Python) is preferred. Candidate should be motivated to learn new skills and research independently and as part of a team. Background knowledge in coastal
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languages such as Matlab or Python. Application Requirements A complete application consists of: Zintellect Profile Educational and Employment History Essay Questions (goals, experiences, and skills relevant