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biomedical data science, developing new methodology and scalable algorithms, and collaborating with interdisciplinary teams at Duke. Duke is an Equal Opportunity Employer committed to providing employment
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a diverse team of biological and chemical scientists Experience with high performance computing environment (HPC) / cluster job submission Knowledge of statistical methods, data science algorithms
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by integrating large-scale single-cell foundation models with structured biological knowledge encoded in genomic graphs. The project will also deliver efficient algorithms to train these models under
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properties of macromolecules, developing novel ways to combine quantum chemical methods and machine learning, developing quantum algorithms for computational chemistry on quantum computers, and applying
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optical simulation skills (Preferably in Zemax) Strong programming skills (preferably in Python) Experience in deep learning algorithms is a plus Ability to work in a highly international team and
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an excellent work ethic and background in molecular simulation and machine learning. Job responsibilities will include: Develop simulation algorithms and software to model challenging gas adsorption behavior in
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, Physics, or a related field; Experience in following and handling international projects; Advanced understanding of deep learning/machine learning algorithms for weather prediction and climate science
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that accounts for ion pairing in a consistent manner Apply the developed equation of state for different applications, including liquid-liquid equilibria, where a robust and sophisticated algorithm may need to be
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collects physiologic and biologic data in extreme environments and utilizes this data to develop novel prediction algorithms of acute mountain sickness, heat exhaustion, cold injury, and other environmental
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terms of universal computational skills. We encourage you to describe your work using broader technical terms—such as "statistical data analysis," "workflow automation," or "algorithm optimization"—rather