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are committed to providing an outstanding training environment and research experiences that will enhance your career and provide an avenue to incorporate your education, expertise, initiative, and dedication
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. graduates (or people about to graduate) with interest in this topic are encouraged to apply. We value diversity of backgrounds and experience, so if you aren’t an expert in all of the approaches we use
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: Experience with mathematical, computational, or statistical modeling Experience developing simulation models, agent-based models, network models, stochastic systems, or dynamical systems Experience with R
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/time management skills, and interest in interdisciplinary collaboration. • Experience in the use of large language models for analyzing text and/or advanced skills involved in analyzing complex
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experiments independently using cells and animal models. Evaluate and interpret collected data and prepare analyses of experimental results to draw appropriate conclusions about the experimental findings. Write
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. The Postdoctoral Associate will design and perform experiments to validate therapeutic targets, develop and test CAR T-cell strategies, and evaluate treatment effects in DMD mouse models. Key responsibilities will
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motivated individual with experience in deep learning and a PhD in computer science, electrical engineering, biomedical engineering, biomedical informatics, biostatistics or a related discipline. Required
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electron microscopy experiments, including STEM, TEM, and related characterization techniques, to investigate the structure–property relationships of energy and quantum materials. 2) Perform advanced data
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. Compliance with all applicable University and departmental policies and procedures. Required Qualifications at this Level Education/Training See job description for education requirements. Experience See job
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ability to work effectively with other team members both in the lab at Duke and with partners from international great ape field sites in Tanzania, Uganda, and Rwanda. Prior experience with large datasets