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developing new machine learning methodologies that tackle unique computational problems in healthcare applications. We use large real-world complex datasets, including data extracted from electronic health
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Preferred Other Computer Applications: SPSS, EndNote Preferred Additional Knowledge, Skills and Abilities: Proficiency in SAS, Microsoft Access, and/or GIS software is highly desired. Email to a Friend https
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technical specifications. Knowledge, Skills, and Abilities: Advanced applied statistics skills, such as distributions, statistical testing, regression, etc. Professional experience developing machine learning
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, behavioral economics, and machine learning, to help policymakers identify and generate evidence on innovative approaches and policy solutions to their most pressing environmental and energy challenges. Job
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skills with experience in cloud data warehouse systems such as Snowflake and data preparation tools like Tableau Prep Experience with predictive modeling, machine learning, AI applications, and advanced
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antibodies and anti-CD20 CAR T-cells form the backbone of treatment for mature B cell malignancies. The project focuses on elucidating changes in gene expression within the tumor microenvironment of chronic
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Associação do Instituto Superior Técnico para a Investigação e Desenvolvimento _IST-ID | Portugal | 4 days ago
establish reference performance and guide the design of more advanced models. The core of the work will then focus on developing and evaluating machine-learning-based NILM methods tailored
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commitment, passion, and excellence in teaching. This position will teach the FinTech 522: Financial Institutions -Statistics course in the FinTech Master’s Program, this required course is made up of two 7
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the use of large language models to support neural network design and data preprocessing. The position involves close collaboration with experts in cardiovascular simulation and Scientific Machine Learning
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cutting-edge research in areas such as pattern recognition, automation science, complex systems, AI for Science, robotics, machine learning, computer vision, natural language processing, biometrics, medical