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to microclimatic variations induced by local vegetation. The researcher will contribute to the analysis of vegetation–climate–technology interactions to optimize energy yield in environments subject to climatic
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language processing, machine learning, artificial intelligence, and human-computer interaction. Established within the School of Computer Science, LTI pioneers innovative ways to understanding, processing, and
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 10 hours ago
. We optimize our partnership with the UNC Health System through close collaboration and commitment to service. OUR VISION Our vision is to be the nation’s leading public school of medicine. We
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optimization algorithms for both estimation and inference. Special emphasis is placed on advancing statistical approaches to address the demands of increasingly complex, high-dimensional, and unconventional data
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the development and optimization of advanced microbiome experimental workflows such as DNA/RNA extraction from complex biological samples, library preparation for next-generation sequencing, and high-throughput
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mathematics, computer science, physics, biomedical or electrical engineering or similar disciplines. Good programming expertise (Matlab, C++, Python or equivalent) and experience with the Linux operating system
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Postdoctoral Associate Required Qualifications: (as evidenced by an attached resume) Ph.D. (or foreign equivalent) in Electrical Engineering, Computer Science, Applied Mathematics, or a closely
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, computational drug repurposing, and de novo design of novel protein-based therapeutics. Our work also includes developing gene editing strategies to correct or inactivate mutations associated with severe
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member's task is strongly intertwined with the tasks of the other team members. You will develop and optimize pioneering in situ 3D ED and 5D ED experiments in a liquid environment. You will minimize
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-based models, particularly for epidemiological applications; 2. Data science and large-scale data analysis in high performance computing environments; 3. Optimization, uncertainty quantification, and