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Field
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chronometabolic research Analysis and quantification of circadian rhythms by rhythm analysis software (Cosinor, JTC cycle, R etc.) Rhythm analysis in human 24-hour time series data and omics data Writing
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working at the University of Arizona and relocations services, please click here . Duties & Responsibilities Develop novel ML / AI models and techniques for analysis of longitudinal time series data
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programming in, for example, R or Python. Particularly valuable is a research background in ecology, biodiversity, systems biology, or related areas, as well as experience working with time-series data, dynamic
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CBS - Postdoctoral Position: Artificial Intelligence Applied to Metabolomics for Health Applications
datasets. Developing explainable AI (XAI) models to facilitate clinical decision support systems (CDSS) and enhance trustworthiness in healthcare settings. Addressing longitudinal and time-series data
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Department: Department of Machine Learning and Data Processing – Faculty of Informatics Deadline: 14 Jul 2025 Start date: preffered September 2025 / by mutual agreement Job type: full-time Job
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will collaborate closely with NSLS-II staff while developing cutting edge sample preparation and data analysis techniques that enable the next generation of the XCFS methodology. In addition
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time series data. Brief Description of Duties: The Postdoctoral Associate will assist the Principal Investigator Dr. Siwei Wang in the department of Neurobiology & Behavior . The incumbent will conduct
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statistical shape analysis, Riemannian geometry, time series and stochastic processes, and Bayesian statistics. Key responsibilities: To carry out research within the framework of the project, under
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for comprehensive systems biology modeling. Identification of causal relationships and biomarker discovery through integrative approaches. Time-series and longitudinal multi-omics data analysis for disease
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in the clinical environment. Writing replicable code for analyzing behavioral and neural data (e.g. modeling behavior, time series analysis, statistical inference). Writing manuscripts to communicate