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available single-cell sequencing data generated from patient samples and mouse models, we will enhance and apply machine-learning based algorithms to deconvolute bulk tumor RNA-seq samples to distinct immune
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genetic knockouts in yeast and mammalian cell lines, and protein purification. Job Responsibilities: 35%: Computational algorithm development and data analysis 35%: Design and conduct experiments with yeast
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 1 day ago
the possibility of reappointment for an additional year. It will involve developing, implementing, and validating novel algorithms for analyzing SWOT data; writing scientific papers; and presenting research
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interdisciplinary teams to apply developed algorithms to real-world datasets and generate valuable biological insights. Perform integrative analyses of multidimensional datasets within the context of basic immunology
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vision, controls, cyber-physical systems and their security, hardware security, and machine learning and their security. The work will include algorithm design, prototype implementation (e.g., in Matlab
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writing C++ and PyTorch. Training and debugging RL agents. Imitation Learning algorithms for robotics or autonomous vehicles. Prior work combining RL with human data or feedback. A track record of code
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programming (e.g., Python, MATLAB). Preferred Qualifications: Experience in resilience analysis for multi-agent systems. Familiarity with communication-constrained algorithm design. Prior work on communication
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., Python, MATLAB). Preferred Qualifications: Experience in resilience analysis for multi-agent systems. Familiarity with communication-constrained algorithm design. Prior work on communication-efficient and
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programming (e.g., Python, MATLAB). Preferred Qualifications: Experience in resilience analysis for multi-agent systems. Familiarity with communication-constrained algorithm design. Prior work on communication
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on applications to complex, dynamic systems. Design and simulate feedback control algorithms for thermo-mechanical systems and related applications. Collaborate with faculty and student teams to support control