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clinical or imaging-based research. Familiarity with vascular imaging software, image post-processing, and AI/machine learning applications in clinical or imaging research is desirable. Demonstrates strong
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. Familiarity with vascular imaging software, image post-processing, and AI/machine learning applications in clinical or imaging research is desirable. Baylor College of Medicine is an Equal Opportunity
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data or large data volumes in all information systems. We contribute methods and algorithms for machine learning, and data mining, including XAI, as well as for data access and query processing. Aarhus
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and associated environmental impacts. Contribute to short-term (2026 to 2030) and long-term (2030 to 2050) verticalisation forecasting models based on machine learning, and to their validation against
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causal analytical foundations of mass transit system performance. The research is expected to contribute both novel methodological advances in statistical modelling, causal inference, and machine learning
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. Mandatory requirements: Demonstrated knowledge of machine learning techniques and programming, with extensive experience in data analysis using Python and R. PhD in Economics, with expertise in health
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. This large multimodal dataset allows us to estimate and test different computational models of the decision and learning processes. One postdoc is currently working on the MEG and iEEG data, and one PhD
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-career scientist to develop cutting-edge machine learning approaches for understanding and designing pathogen antigens. This is a unique opportunity to help shape a new research program at the intersection
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within the Texas Children's Cancer Center. The project aims to develop and test novel CAR-redirected immunotherapy for pediatric solid tumors. In particular, gene knockout and knock-in screens will be
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in tropical regions; analyze links between macrofauna and soil carbon; build/validate scoring algorithms using machine learning/cumulative functions. Outputs – Lead scientific, technical, and policy