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Proficiency with high-parameter flow cytometry Familiarity with bioinformatics workflows (e.g., single-cell RNA-seq analysis) Strong background in cell culture, molecular cloning, viral transduction, and
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) for dynamic systems with unknown but measurable performance functions. Experience in system identification and online time-varying parameter estimation algorithms. Programming skills in MATLAB/Simulink, C/C
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improved performance in tasks of systems analysis like parameter estimation, solving inverse problems, and uncertainty quantification. The successful candidate will join a multi-institution research team
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parameter space, and using and/or developing agent-based models for the movement and behavior of fish in rivers. Presenting material at conferences, writing research papers for publication, and/or assisting
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, developing and numerically solving diffusion reaction equations, parameter estimation, machine learning, and sensitivity analysis, with an emphasis in building open-source technologies that benefit the entire
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descent, random forests, etc.) and deep neural network architectures (ResNet and Transformers). Preferred Qualifications: Knowledge of Approximate, Local, Rényi, Bayesian differential privacy, and other
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 10 days ago
Dependent on Qualifications/Experience Proposed Start Date 02/01/2025 Estimated Duration of Appointment 12 Months Position Information Be a Tar Heel! A global higher education leader in innovative teaching