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on the development of new methods integrating a variety of data types (remote sensing, geology, geophysics, geochemistry) for geological modelling and advanced exploration targeting of mineral deposits
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Experience with machine learning, data mining and data assimilation is a plus Knowledge of git, docker, kubernetes, and/or metadata is a plus Ability to work within a team Excellent interpersonal and
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of AI models and LLMs specifically tailored for data mining in the physical sciences and engineering Fine-tuning and evaluation of open-source LLMs (e.g., Teuken 7B, Llama 3, Mistral 7B) specifically
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drainage, cultivation, and mining. As these areas constitute major sources of carbon dioxide emissions, accurate mapping is crucial for their effective restoration and management. Peatlands are highly
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drainage, cultivation, and mining. As these areas constitute major sources of carbon dioxide emissions, accurate mapping is crucial for their effective restoration and management. Peatlands are highly
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, proteomics, lipidomics and metabolomics in large-scale human populations. The lab is interested in integrating and mining the different types of data to understand the genomic causes and other biomarkers as
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Strong background in SEM, FIB, EDS, RAMAN, LC-MS/MS, and FTIR Proficiency in data analysis and data modeling Excellent written and communication skills with demonstrated records of publications. Strong
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assists them to identify career opportunities in Northern Nevada. Dual Career Assistance Program Department Information The Chemical and Materials Engineering Department is a vibrant, growing place to work
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analytics in the areas of health care, social issues, text, and social media, and faculty members have developed key methodologies in data mining, social-network analysis and mathematical optimization
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platforms for integrating spatial and temporal information, harnessing remote sensing data, using climate information, understanding fuel accumulation and running physics-based or data-driven wildfire