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Field
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A postdoctoral position is available for highly motivated individuals with a background in Computational Neuroscience to analyze complex time-series data from ongoing 2-photon microscopy experiments
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related field. The ideal candidates will have experience in one or more of the following topics: deep learning for image and point cloud data processing, deep learning for time series data prediction
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complements LCAB’s research programmes. High competence in the analysis of large ecological and other data sets and time series. Ability to write up research for publication in high profile journals, along with
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in time series, tensor data analysis, and related topics. Duties include identifying important problems and novel approaches related to analysis of tensor and other complex time series and related
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will deploy moored sensors (e.g. acoustic Doppler current profilers - ADCPs) in a series of submarine canyons in the Gulf of Mexico and along the US East Coast. Time-lapse bathymetric surveys and
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models, attention mechanisms, and foundation models. 3) Time-Series Analysis : Specializing in modeling, forecasting, and anomaly detection to address complex real-world challenges. The successful
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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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analyzing complex time series data. Brief Description of Duties: The Senior Postdoctoral Associate will assist the Principal Investigator Dr. Siwei Wang in the department of Neurobiology & Behavior
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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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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