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, Neuroscience Posting Number req27102 Department Neuroscience Department Website Link https://neurosci.arizona.edu/ Location Tucson Campus Address Tucson, AZ USA Position Highlights The Maurer laboratory
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and the various components of the tumour microenvironment. The research will primarily be conducted using patient-derived glioblastoma models and will combine approaches from cell and molecular biology
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Sciences Location Bloomington Position Summary Position Overview The Postdoctoral Researcher will join an NSF-funded project developing and testing computational models of how decisions evolve over time. The
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/10/2024 Department Art and Design Line Number temporary service Budget Title Artist's Model Rank/Grade NS FTE Part-Time FLSA Non-Exempt Negotiating Unit PEF Appointment Type Temporary Jurisdictional
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generative models of how human tissues develop, mature and regenerate, and of what goes wrong in disease, with a focus on child health. The group starts in January 2027. You will develop generative models
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-sensing-and-modeling-of-the-cryosphere Where to apply Website https://www.jobbnorge.no/en/available-jobs/job/308033/postdoctoral-research-fel… Requirements Research FieldGeosciencesEducation LevelPhD
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. Quantify uncertainty in models and assess the impact on long-term geothermal reservoir performance and development decisions. The project is funded by Eni S.p.A through the UK Energy Futures (https
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curated pharmaceutical science and public health databases that can be used for modeling purposes. Information about Dr. Zhu’s research and recent publications can be found on his lab website: https
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ALMA MATER STUDIORUM - UNIVERSITA' DI BOLOGNA - - DIPARTIMENTO DI INGEGNERIA INDUSTRIALE | Italy | 9 days ago
Description The project aims to develop, validate, and apply original models and methods for the design, management, and optimization of material-handling solutions and four-way shuttle-based automated storage
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, to develop solutions for predicting risk in international-scale financial markets. The project is developing event-triggered artificial intelligence approaches that complement existing financial risk models