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美国纪念斯隆-凯特琳癌症中心招收计算免疫肿瘤学博士后

2020年08月12日
来源:知识人网整理
摘要:

美国纪念斯隆-凯特琳癌症中心招收计算免疫肿瘤学博士后

We are seeking highly motivated postdoctoral fellows to join Dr. Benjamin Greenbaum’s new laboratory at Memorial Sloan Kettering Cancer Center in New York. We are establishing a new program in the field of Computational Immuno-Oncology, bridging computational and immune oncology, motivated by using multiomic data and new computational tools from fields such as machine learing, evolutionary biology, and statistical physics to utilize datasets at MSKCC to better understand productive immune recognition of tumors and patient response to immunotherapies. Trainees in this new endeavor will help define quantitative approaches to cancer immunoloy. The lab focuses on quantitative biology at the intersection of cancer research, immunology, evolutionary biology, and virology. In particular we are interested in understanding the impact of tumor-immune interactions and immune ecology on tumor evolution. We are seeking early career scientists with research expertise and interest in computational biology and bioinformatics to lead projects around these topics in close collaboration with experimental and clinical investigators. Applicants should have an interest in quantitative approaches to cancer immunology and tumor evolution. Applicants must possess a PhD in relevant discipline such as computer science, physics, bioinformatics, evolutionary biology, and computational biology and have a demonstrated publication track record. Candidates seeking an academic or industry career are encouraged to apply. A research background in cancer evolution and immunology would be considered an asset.

Interested candidates should send a cover letter indicating the reason for the application, curriculum vitae, and the names and contact information for 3 references to Yesenia Werner at CompOncBST@mskcc.org. Dr. Greenbaum’s lab is located at 321 East 61st Street, New York, NY 10065.

Learn more about the Computational Oncology service at: http://www.CompOncMSK.org