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other researchers. Support the implementation of hardware and software, standard operating procedures, and contribute to the optimization of workflows. 5%: Other special projects and duties to support
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calculations, geometry optimization, and prediction of NMR parameters will be considered an advantage. The candidate should have excellent written and oral communication skills, strong organizational ability
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optimization, and development of tools suitable for high-performance computing environments. Experience with parallel computing and workload management systems such as SLURM is highly desirable. Model
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safety assessment of insect-derived products. Experience with aquafeed formulation software and least-cost diet optimization. Proficiency in R, SAS, or equivalent for statistical analysis of biological
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: Design and optimization of graphene edge to edge tunning device structures, and electronic signal detection. Design and test of microfluidic structures in combination with the tunneling device. Taking
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 2 months ago
learner development in a diverse, respectful environment where our colleagues demonstrate professionalism, enhance learning, and create personal and professional sustainability. We optimize our partnership
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 26 days ago
learner development in a diverse, respectful environment where our colleagues demonstrate professionalism, enhance learning, and create personal and professional sustainability. We optimize our partnership
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approaches to experimental design, data analysis, statistical testing, and data visualization. Establish, optimize, validate, and troubleshoot experimental protocols. Maintain complete and accurate
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biology approaches, to uncover novel immune cell states and therapeutic targets. Develops and optimizes experimental protocols for cellular immunology, including trajectory inference and dimensionality
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of neural networks, information-theoretic and optimal-transport perspectives on representation and generalisation, probabilistic numerics and Bayesian deep learning, and emerging frameworks for scientific