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://fa.oregonstate.edu/stu-manual/500-employment-eligibility-requirements Must be academically enrolled in a high school, community college, or university and pursuing a program or course of study Must meet Academic
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interested in computational materials design and discovery. The successful candidate will develop new, openly accessible datasets and machine learning models for modeling redox-active solid-state materials
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solutions, buffers, and media. Gathers, organizes, enters, and analyzes data; perform literature searches on computer and retrieve literature from library. Incorporates new information/techniques
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structured and unstructured data, such as text, images, and videos. Additionally, there are individual machines available, each with high-performance GPU cards for enhanced processing capabilities. Various
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proficiency. Preferred Qualifications: Prior knowledge and experience in at least three of the following: working with high-performance and cloud computing, programming in Python, data analysis and
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coding in R, Matlab and/or Python, and already adapt to using the UNIX command line and executing analyses using high performance computing cluster. Preferred qualifications: Prior experience in analyzing
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(SUNBIRD) to validate blood biomarkers for Alzheimer’s disease in a large clinic-based cohort. This position is a member of a multidisciplinary research team and performs a variety of research, data base
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team to lead our efforts to improve quantitative image analysis in projects related to cell adhesion. This position will operate with a high level of autonomy and entails developing innovative
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Initial term: 1 year, with the possibility of extension based on performance and funding Location: Houston, TX and San Antonio, TX Job Duties Conducts qualitative data collection (ethnographic observations
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will I be doing? Refractory metals (Mo, Nb, Ta, W, and Re) are promising materials for high temperature structural applications as a result of their high melting points and high strengths. Additive