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psychoactive substances, in seized drug products or clinical samples. The candidate will have the opportunity to work directly with experimentalists to validate predictions made by their machine-learning models
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research to systematically understand cancer biology, identify diagnostic and prognostic biomarkers, and improve cancer therapy. Projects will involve the development of AI solutions, including machine
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experience and enhanced potential to receive an ERC Starting Grant in the future. Open to both PhD (natural sciences) and MD (medical sciences) holders. From a variety of academic backgrounds: molecular
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and Fluidigm technologies at UTHSC. Qualifications PhD in Computer Science, Electrical Engineering, Biomedical Engineering, Statistics, or a related field. Strong background in machine learning, data
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Experience with machine learning, data mining and data assimilation is a plus Knowledge of git, docker, kubernetes, and/or metadata is a plus Ability to work within a team Excellent interpersonal and
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Postdoc position (f_m_x) ,,Combining Physics-Based Machine Learning and Global Sensitivity Analys...
“Geosystems”), we are looking for a: Reference Number 10337 Are you seeking a PostDoc project at the interface between geoscience, machine learning and mathematics – with an application to the highly relevant
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Infrastructure Engineering. Undergraduate and graduate degrees (Master and PhD) are offered in civil & environmental engineering, computer engineering, electrical and electronic engineering, and mechanical
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Postdoctoral researcher (f_m_x) - Waves in the Inner-magnetosphere and their Effects on Radiation...
of the adverse effects of the space environment utilizing satellite observations, physics-based numerical models, machine learning, and data assimilation. Our research will help safely design and operate