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across tissues, over time and upon perturbation for translational benefit, leveraging tissue profiling through multiomic technologies in conjunction with cutting-edge computational and machine learning
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and stress level is moderate to high. Noise level is quiet to moderate. Physical Activities Ability to work in front of a computer for extended periods of time. Occasionally required to move about the
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computing environments, workflow-management systems, containers, and/or software development practices. Experience with machine learning, predictive modeling, or artificial intelligence methods applied
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, and be able to communicate effectively with collaborators and team members This position will be based at Duke University in Durham, NC. Be Bold. The postdoctoral associate will work on several ongoing
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Researcher will work in Professor Benjamin Peherstorfer’s group (https://cims.nyu.edu/~pehersto/ ) on scientific machine learning at the Courant Institute of Mathematical Sciences where they will help
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Do you want to combine high-throughput directed evolution with machine-learning analysis of deep sequencing data to engineer better antibodies? The Sormanni Lab in the Department of Chemical
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the Department of Neurology, Duke University School of Medicine is looking for a highly-motivated postdoctoral candidate who is passionate about neuroscience and disease-related research to study the underlying
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autonomous, closed-loop (“self-driving”) laboratory workflows. The role integrates catalyst synthesis, high-throughput reactor testing, and in situ/operando characterization with machine-learning and agentic
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) develop multimodal machine learning models and methods to determine signatures and biomarkers to understand mechanisms distinguishing spontaneous versus precipitated withdrawal episodes. The spontaneous vs
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with in vivo electrophysiology and/or calcium imaging data collection and analysis. Experience with machine learning–based behavioral quantification (e.g., DeepLabCut, MoSeq). Experience with MATLAB