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to iteratively refine models and optimize experimental design. Collaborate with another postdoc in the NIH Center to use scientific machine learning (SciML) to automatically select mathematical models from data
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, audio, pose, sensor, or behavioral data. Experience developing machine learning models for human behavior analysis. Interest in autism research, developmental science, digital health, or behavioral
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discoveries made in the laboratory with meaningful improvements in patient care. You will be part of a research environment that values curiosity, creativity, scientific rigor, and continuous learning while
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model for education and professional nursing practice Role models and promotes the concept of life long learning Leads committees, work groups and/or projects related to the implementation of educational
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, organization, and function; models of perception, cognition, learning, and behavior; and statistical and machine-learning approaches for understanding neural data and brain function. We are particularly
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. Knowledge of survival analysis. Knowledge of machine learning methods. Other Requirements Application materials must include: Curriculum Vitae (CV) Statement of research interests Names of three professional
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to changing requirements and environment Hands-on problem-solving skills Experience with creating 3D models using CAD software Experience with 3D printing (SLA, MJP, SLS, PolyJet, FDM) Experience designing and
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), maintain and fine tune machine learning models for predicting treatment preferences of dementia patients, assist Sinnott-Armstrong in designing and creating two new, innovative courses to be taught in
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: Relocation Assistance: Up to $10,000 Total Rewards: A comprehensive set of pay and benefits designed to support your well-being, professional growth, and work-life balance. Learn more here . Manage and
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develops next-generation human disease models and therapeutic discovery platforms by integrating stem cell biology, patient-derived organoids, organ-on-chip technologies, high-content imaging, multi-omics