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→ cell → patient Integrate multi-modal data (genomics, transcriptomics, biosensors, EHR) Perform single-cell and spatial multi-omics analyses at scale Lead high-impact publications and contribute
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to computational materials, mechanics, or related fields Proven ability to work collaboratively in an interdisciplinary research environment and mentor graduate students. Experience with high-performance computing
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Center for Biologics Evaluation and Research (CBER) | Silver Spring, Maryland | United States | about 5 hours ago
scientific data, including large-scale omics datasets, within high-performance computing (HPC) environments. Learning Objectives: Under the guidance of a mentor, you will gain skills in and learn to: Develop
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Programming Systems R&D: Contribute to DOE goals of enabling performance‑portable high‑productivity languages (Python/Julia/Rust) and evaluate the emerging role these languages and frameworks within scientific
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to visualize key performance indicators, patient volumes, and program outcomes for stakeholders. Develops dashboards for program operations and research. Designs and develops statistical analysis for research
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, data visualization, high performance computing, and AI/machine learning. Student Assistant will also assist with HPC instruction. Required Minimum Qualifications: Current University of Alabama
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the data from HEP experiments is strongly required Programming expertise in Python and either PyTorch or TensorFlow is required Experience using High-Performance Computers (HPCs) is preferred Ability
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on department or program needs without changing the general nature and scope of the job or level of responsibility. Employees may also perform other duties as assigned. Physical Requirements*: Frequently stand
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. Develop skills in coupling crop and hydrology models at watershed scales. Gain experience validating models using large, multi-source datasets. Learn to apply high-performance computing and machine learning
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relevant to high-field and high-temperature dielectric performance to inform the digital discovery of new polymers. Characterize materials, interfaces, and film morphology using microscopy and materials