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flexible fitting of mechanistic and statistical models to the data. Our current focus is on generating datasets of sufficient size and diversity to train machine learning models to accurately predict how
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of health equity. Learn more: https://hospital.uillinois.edu/about-ui-health This position is intended to be eligible for benefits . This includes Health, Dental, Vision, Life Insurance, a Retirement Plan
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technologies, and cloud platforms. Support researchers’ use of AI and machine learning tools, including AI coding assistants and agents (e.g., Claude Code), model APIs (e.g., Anthropic, OpenAI), and open-weight
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Proficiency in Cadence Proficiency in Python and Matlab Experience in implementing algorithms for machine learning Good written and oral communication skills We regret to inform you that only shortlisted
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machine learning-based model to map satellite retrievals to ground based air pollutant concentrations Conducting error assessment on the derived concentration data Implementing new observational data
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Instituto de Ciência e Inovação em Engenharia Mecânica e Engenharia Industrial | Portugal | 3 months ago
to accelerate technological maturity (TRL), validation, and the transfer of scientific results. Main Responsibilities: Application of advanced Machine Learning, Deep Learning, reduced-order models, and physics
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such as transformers, self-supervised learning, multimodal learning, generative models, graph neural networks, or foundation models. Experience with structural and/or functional brain modeling. Familiarity
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data science approaches includes the application of Bayesian inference or probabilistic machine learning to geophysical models. UiO is subject to the Security Act, which governs the organisation's
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-computer interaction and design; automated self-driving laboratories that pair hardware instrumentation with active-learning machine learning for experiment design to accelerate chemistry, materials, and
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% of your time), including tutorials and supervision of Bachelor’s theses. This is what we ask of you This is an interdisciplinary project that combines machine learning and AI, probabilistic risk