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Field
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data sets and climate model outputs Analytical skills, including experience with multivariate analysis, time-series, and geospatial statistics Previous research experience and publication record Ability
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asphaltene precipitation and the onset temperature of paraffin crystal formation, phenomena of great relevance to the oil and gas industry. Our group has recently established a laboratory specifically designed
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-series data analytics IoT and wireless communication Goal-oriented semantic communication Edge intelligence and resource optimization Strong command of machine learning with hands-on implementation
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related fields. Skilled in operating and troubleshooting trace gas analyzers, sensors, and/or automated sampling equipment. Ability to analyze time series data (or reasonably learn) using scientific
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for LLMs. Experience with time-series data, anomaly detection, or predictive maintenance is a strong plus. Familiarity with industrial datasets and domain-specific challenges is desirable. Excellent problem
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-series photometry, spectroscopy, astrometry, Bayesian/statistical inference, and/or software development for astronomical datasets. Department Contact for Questions Songhu Wang (sw121@iu.edu) Additional
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of coatings formulation both through deterministic mathematical models and through use of artificial intelligence. Responsibilities and qualifications Your overall focus will be on strengthening
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. Produce a series of interactive data visualisations to visually model the system and its core components, barriers, and opportunities for improving access. Critically assess higher education equity
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one or more of the following topics: Computationally intensive methods in Statistics such as Count Time Series, Curve estimation, Environmental Statistics, Forensic Statistics, Stochastic Modelling
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architectures, attention mechanisms, and fine tuning techniques for LLMs. Experience with time-series data, anomaly detection, or predictive maintenance is a strong plus. Familiarity with industrial datasets and