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. In this role, you will collaborate with leading experts in autism research, computer vision, machine learning, psychiatry, and developmental science to develop innovative technologies that improve
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program focused on development of machine learning tools and their applications to medical imaging. Key Responsibilities: The Post Doctoral Associate will apply their technical skills toward the
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imaging and patient care. You will join a highly collaborative, interdisciplinary research environment focused on developing and applying cutting-edge machine learning and deep learning methods to
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clinical settings. The postdoctoral associate will contribute to methodological development and applied research in machine learning, statistical modeling, natural-language processing, epidemiology
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engineering, machine learning, and translational biomedical science. Develop modular software tools, simulation frameworks, and machine learning pipelines to support biomarker discovery and validation
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required. Preferred Qualifications: Experience with large-scale or high-dimensional datasets (e.g., cohort, registry, or omics data) Familiarity with causal inference methods or machine learning
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with hierarchical modeling and mixed effects models. Knowledge of survival analysis. Knowledge of machine learning methods. Other Requirements Application materials must include: Curriculum Vitae
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data integration and systems biology. Computational biology, bioinformatics, machine learning, or artificial intelligence. Drug screening, pharmacology, or precision oncology. Advanced microscopy