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preclinical models and retrospective human MTLE datasets. Apply complex signal-processing approaches to analyze animal and human intracranial EEG. Develop and implement computational network analyses
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models for multiple chronic diseases in real-world data and cohort studies. To successfully work in this position, experience of data-driven analytical approaches, machine learning and advanced
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focus is on bridging gaps in data quality, model generalizability and market scalability. This groundbreaking initiative aims to advance pathology practices by developing artificial intelligence systems
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design of formulations and drug delivery systems for small molecules, biologics, nucleic acids, and advanced therapeutics. Biopharmaceutical performance: Mechanistic and data-driven modeling of drug
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National Aeronautics and Space Administration (NASA) | Pasadena, California | United States | 19 days ago
inform representations and encoder adaptations. This activity will provide hands-on experience in making three-dimensional vegetation structure accessible within data-driven geospatial modeling processes
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data analysis, and artificial intelligence for medical sensing systems Modeling, simulation, and analysis of biophysical processes as well as medical sensing and communication systems Development
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, develop, and optimize modern analytics capabilities that leverage enterprise data platforms, automation frameworks, large language models (LLMs), retrieval-augmented generation (RAG), and enterprise
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, including emerging life-sciences foundation models, to investigate cancer aetiology, identify biological and clinical subtypes, and develop robust models of cancer risk that can inform prevention, screening
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are the largest and most important part of KUNM’s revenue model. Individuals who contribute to KUNM are considered “members" of the station. Reporting to the Director of Development and overseeing a team of two
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mathematical models to address fundamental questions in biology. Examples of research topics include but are not limited to: development of new AI architectures for biology and hybrid models that combine deep