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position as Postdoctoral Fellow in law at the UiS School of Business and Law, Department of Accounting and Law. The Postdoctoral Fellow will be affiliated with the research project AUTO-MARE – Autonomous
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candidate to develop Machine Learning models and frameworks for time series analysis, aimed at understanding how the human brain encodes information. This cross-disciplinary project is a high-level
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behaving mice, and advanced modeling + machine learning analyses. Please read more about our research at www.apostolideslab.org . Key questions we want to answer are: How do neural circuits extract
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Information , Data Visualization , Deep Learning , High dimensional Data , Large Language Models , Large Scale Optimization , Machine Learning , Natural Sciences , Public Interest Tech Computational Biology
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phenomena and impulsive events in the solar atmosphere. Our approach includes the implementation of machine learning models for multiline full-Stokes inversions. About the person: The successful candidate
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or predictive modelling, edge AI, AI for biomaterials formulation, processing and manufacturing optimization. Wearable devices – wearable physiological sensors, smart textiles, soft robotics, and exoskeletons
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denotational semantics, abstract machines, as well as string diagrams and graph rewriting. Some knowledge of category theory would be useful but not essential. Being able to formalise the frameworks and
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staff position within a Research Infrastructure? No Offer Description As a University of Applied Learning, SIT works closely with industry in our research pursuits. Our research staff will have the
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publication record. Outstanding data analytics, mathematical, and computer modelling skills. Excellent interpersonal communication and oral presentation skills in English Self-driven and strong team spirit Open
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assays, complemented by mass-spectrometry-driven chemical profiling and machine-learning-supported multivariate analysis. Where relevant, CRISPR-Cas-based genetic perturbations in mammalian cell models