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cutting-edge theories, methods, and computational tools for integrating large-scale, heterogeneous biomedical data across multi-institutional research networks, with a focus on the analytical and
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without reasonable accommodation. Preferred Qualifications Experience with generating or analyzing large-scale genomic data. Excellent written and oral communication skills. Message to Applicants Central
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$77,047, depending on qualifications, experience, department budgets, and industry data. Employees receive more than just a paycheck. University employees enjoy a comprehensive benefits package that
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methods to biological problems Experience with database querying, management systems, and data extraction techniques for large datasets Knowledge of natural language processing (NLP) and/or large language
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interatomic potential to incorporate materials response . Resulting models are implemented in LAMMPS and are used to perform ML-accelerated large-scale dynamics simulations to investigate the evolution
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. This research will leverage advanced 'omics' technologies and 'big data' analytics to unravel complex pest-natural enemy interactions, understand host associations, and identify adaptation mechanisms at a
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, epidemiology, health informatics, population health sciences, or a closely related area is required. Experience: Experience in cleaning and analyzing large-scale real-world data, such as Medicare claims and
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. Responsibilities* Project Specific Responsibilities: Conduct human-participant experiments, including behavioral paradigms, neuromodulation procedures, and physiological data acquisition Analyze large-scale and
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Center for Drug Evaluation and Research (CDER) | Silver Spring, Maryland | United States | 6 days ago
against new data, target organs tags will be generated for all SEND datasets, enabling large-scale analysis of the relationships among toxicology study endpoints, organ system toxicities, drug
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. Data management skills and demonstrated experience managing, standardizing, synthesizing, and visualizing large, disparate natural resource (e.g., forest inventory, climate, land use, soils, elevation