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industrial objects. Depending on the object characteristics and quality requirements, different capture systems are applied. Image-based acquisition of the current state of arbitrary object geometries has
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, Bayesian statistics, epidemiology, causal inference, statistical learning, artificial intelligence (AI), high-dimensional data, and/or electronic medical records are encouraged to apply. Successful
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well as challenges including imperfect detection and missing data. Approaches required may include Bayesian methods with informative priors. Interprets and draws conclusions from analyses that will be used to inform
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to detect anomalies in evolving data. Some of them consider scenarios where streaming objects with one or multiple features have causal/non-causal relationships with each other which can be represented as
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NIST only participates in the February and August reviews. NIST has recently launched a program to develop high accuracy 3D thermal imaging and control using thermosensitive magnetic nano-objects
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. At the core of data literacy is the ability to detect patterns and trends, or identify outliers and anomalies from data. However, these requirements often rely on visualisations, which creates a severe
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datasets. Proficiency with geometric morphometrics and image alignment. Proficiency in applying quantitative genetic methods to large datasets. Proficiency with large-scale animal models using Bayesian
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opportunity to shape the future of medicine. Job Description Our laboratory studies breast and ovarian cancer, striving to discover the mechanisms behind disease initiation, progression and drug resistance. We
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RAP opportunity at National Institute of Standards and Technology NIST Advancing Drug Detection and Identification for Public Health and Harm Reduction Location Material Measurement Laboratory
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hypotheses and computational analyses. Integrate genetic, molecular, and clinical features to identify mediators linking genotype to phenotype using mediation and causal inference frameworks (e.g., Bayesian