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, applying analytical rigor and statistical methods, and driving toward actionable insights and novel solutions Expertise in causal inference and machine learning is desirable but not necessary This position
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experience in developing competitive national and international research applications Experience in programming languages (e.g. Python/R) and analytical skills in model evaluation Experience in advanced
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UT Arlington and Shimadzu Scientific Instruments) that offers extensive resources for advanced imaging, mass spectrometry, proteomics, and analytical chemistry. The Department also benefits from access
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, XRD, SEM, TGA, BET). Good Knowledge of agronomic tests and design of experiments (DOE). LCA basics Track record of publications in peer-reviewed journals. Strong analytical and problem-solving skills
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platforms and hardware. Knowledge of machine learning and signal processing techniques. Excellent written and verbal communication skills in English. Strong analytical and problem-solving abilities
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. Robust analytical and written communication skills, including proficiency in presentation and educational content development. Proficiency in MAXQDA, Dedoose, or other qualitative software. Detail-oriented
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variety of scientific principles and theories. Maintains substantial knowledge of state-of-the-art principles and theories. Develops advanced analytical models and systems and provides solutions and
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disparities in supportive care medication (SCM) use, using national datasets (e.g., SEER-Medicare, SEER-MHOS), predictive analytics, and stakeholder-engaged methods. The lab is committed to actionable research
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. Qualifications Ph.D. in Physics, Materials Science, or a related field. Hands-on experience with cleanroom nanofabrication. Familiarity with transport experiments (thermal, electrical) is a plus. Strong analytical
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implement MR-based simulation platforms for training and process enhancement in remote construction. Apply machine learning techniques for optimizing construction assembly processes, predictive analytics, and