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minimum of one year eligibility remaining. Strong skills in technical programming languages, e.g., Matlab, Python, or C++; in computational statistics, i.e., unsupervised and supervised ML methods, incl
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– Coordinating with and assisting the PI in the design of experiment and grant proposal methodology as well as methods for analyzing the results of experiments. 2. Research Publications – Preparation of text
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– Coordinating with and assisting the PI in the design of experiment and grant proposal methodology as well as methods for analyzing the results of experiments. 2. Research Publications – Preparation of text
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Dr. Adam Coates and includes Drs. Carrie Fearer, Verl Emrick, and Mark Ford as Co-PIs. Goals for this project include: (1) Inventory of fuels, using traditional transect methods and terrestrial laser
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-learning methods, knowledge-graph and ontology-based scientific data infrastructures, and agentic workflows for autonomous hypothesis generation, mechanistic exploration, and design of catalytic systems
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computational background. • Proficiency in spike train analysis and neural decoding methods. • Advanced programming skills in MATLAB, Python, or R. • Experience with surgical procedures and in vivo recording
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supervision of Prof. Yingda Cheng on computational methods and modeling for kinetic equations. The research conducted will involve development of numerical methods, development and analysis of reduced order
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government partners, we conduct cutting-edge research on paper-coating technologies using aqueous spray-coating methods to address emerging challenges in food and healthcare packaging. We are seeking a highly
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of quantum error correction, tensor networks, and/or machine learning. Experience with programming and numerical methods is preferred. Overtime Status Exempt: Not eligible for overtime Appointment Type
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Forest Sector Industry: A Mixed-Methods Approach.” This interdisciplinary research initiative integrates stakeholder engagement, market analysis, and policy evaluation to develop a strategic