61 parallel-computing-numerical-methods-"Simons-Foundation" research jobs at Duke University
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an excellent opportunity for recent graduates interested in applying quantitative and computational methods to biomedical research, particularly in immunology. Job Duties Develop and analyze mathematical models
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learning, or related quantitative field. • Proficiency with deep learning frameworks (e.g., PyTorch, TensorFlow, and JAX). • Experience in PDE/ODE modeling and numerical methods. • Strong interest in
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skills. Preferred Qualifications: Prior research experience in computational biology, mathematical modeling, or immunology. Familiarity with numerical methods, parameter estimation, and data visualization
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deep learning frameworks (e.g., PyTorch, TensorFlow, and JAX). • Experience in PDE/ODE modeling and numerical methods. • Strong interest in interpretable ML and mechanistic model discovery. Submit a
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). Experience in interdisciplinary team-based research. Preferred Qualifications: Prior research experience in computational biology, applied mathematics, or quantitative biology. Familiarity with numerical
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will contribute to developing and evaluating state-of-the-art methods for predicting mental health outcomes from multi-modal clinical and digital health data. This position offers the opportunity to work
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computational methods for the analysis of genomic, single-cell, and/or other high-dimensional biological datasets. Integrate multi-omics data (e.g., genomics, transcriptomics, proteomics) to identify novel
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. Postdoctoral Associate – Psychiatry – Behavioral Medicine – Shelby Lab Be You. The Cancer Symptom Management and Support Program is seeking a Postdoctoral Associate for a position beginning in September 2025
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develop novel imaging methods, in part through a rich group of collaborations across the Medical Center and University. The Post Doc Associate will conduct independent research activities under the guidance
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, with a particular emphasis on Urban Resilience to Climate Risks. Current research themes include: • Adaptation of People: Leveraging big data and computational methods to analyze adaptation behaviors and