43 high-performance-computing-postdoc Fellowship positions at Nature Careers in United States
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-performance computing clusters (>105,000 processors). This unique interdisciplinary environment emphasizes the integration of AI in life sciences, offering an outstanding platform for recent Ph.D. graduates
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innovative, high-impact research. A two-year joint post-doctoral training program between the Division of Population Sciences at Dana-Farber Cancer Institute and the Richard A. and Susan F. Smith Center
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The Neuro-Oncology Branch (NOB) at the National Cancer Institute’s Center for Cancer Research (CCR) is a specialized program dedicated to advancing the study and treatment of brain and central
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backgrounds, and design programs to promote public health particularly among high-risk and underserved populations. We conduct groundbreaking research that advances treatment, we educate tomorrow's physician
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advancing understanding and treatment of pediatric cancer. Dr. Brian Crompton’s lab is an interdisciplinary team with both computational and wet bench scientists that utilize omics (e.g. genomic, epigenomic
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apply cutting-edge biomedical technology to empower cancer research. Successful candidates will join our team to contribute to the following project: a) Assessing ultra-high dose rate radiation therapy
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health particularly among high-risk and underserved populations. We conduct groundbreaking research that advances treatment, we educate tomorrow's physician/researchers, and we work with amazing partners
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approach is transdisciplinary, transformative, and co-creative. The RIFS awards the Klaus Töpfer Sustainability Fellowship as part of its Fellow Programme. Prof. Dr Klaus Töpfer was the Founding Director of
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, preventing cancer at the community level, identifying and evaluating cancer risk in high-risk populations, and measuring the quality and outcomes of cancer therapy. We invite applications for a fellowship
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fellow to join our translational research program in macrophage biology/immunology. Our team takes a systems approach—integrating multi-omics, network science, machine learning, and comprehensive in vitro