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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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to discover new therapies. The successful candidate will assume a leadership position within the lab as a Postdoctoral Associate. Set the tone for both scientific and scholarly excellence. Drive forward complex
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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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colleagues working on prehistoric Cyprus on the island and across the globe. The research should lead to a series of substantial research papers and the creation of a robust datasets on food and feasting
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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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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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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