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美国国立卫生研究院（NIH）国家图书馆 （NLM）江晓芳课题组诚聘生物信息学博士后
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课题组介绍： 江晓芳课题组位于美国首府华盛顿城郊的NIH bethesda校区, 依托NIH顶尖的生物医学资源，致力于用计算和大数据方法来研究细菌、微生物与疾病和健康的关系。实验室的首要目标是开发计算工具和方法，促进人类对微生物和病毒进化的理解，并帮助开发基于微生物的诊断、治疗和预防策略。 课题组于2019年筹建，学科带头人江晓芳博士在生物信息学领域有所建树，曾以一作和通讯作者身份发表论文30余篇，包括Science在内的高水平论文。论文被引用3200余次，H-index为 23 ，i10-index 为25。具体请关注课题组网页https://www.ncbi.nlm.nih.gov/CBBresearch/jianglab/. 一直以来，NIH对博后待遇优厚，NLM尤其如是。科研人员不仅可以获得丰厚的科研资金、工资福利，还可充分享用全球最先进的生物医学数据和信息系统以及高性能的计算资源，信息系统以及高性能的计算资源，具有广阔的个人发展前景。目前，有两个博后职位开放，欢迎有兴趣的人员加入！ 岗位待遇： 工资67,400美元每年起，附加NIH提供的优质保险与福利，年薪视工作年限和绩效调整，随工作年限上涨。 岗位要求: Position in Microbial bioinformatics Description: The selected candidate will be able to contribute to the ongoing projects in the lab, as well as develop their own independent research projects in microbial bioinformatics. Several projects are currently available including 1) identifying and characterizing microbial gene clusters of interest; 2) knowledge-based functional annotations of biosynthesis pathways; 3) building phage and bacterial interaction networks. Qualifications: We are looking for creative, self-motivated individuals who are interested in applying computational tools to challenging problems in large-scale microbial genomic analysis. Applicants who meet the following requirements will be considered for the positions: ● A Ph.D. with less than 5 years of postdoctoral experience ● Ph.D. in Bioinformatics, microbiology, virology, or a related discipline with intensive training/experience in bioinformatics. ● Strong proficiency in Python, R, and Bash ● Strong oral and written communications skills; ● With a proven track record in this area reflected in recent or pending publications. ● A clear sense of organization, purpose, and accountability Prior experience in at least three of the following computational areas: ● Protein structure modeling and prediction ● Structural bioinformatics ● Comparative genomics ● Metagenomics analysis ● Large-scale genomic data analysis ● Evolutionary genomics Position in Microbial genomics: machine learning and statistics Description: The selected candidate will be able to contribute to the ongoing projects in the lab, as well as develop their own independent research projects. Several projects are currently available including 1) Deep learning for novel protein family classification; 2) Constructing probabilistic models for co-occurrence analysis based on interaction network 3) Computational tool development to interpret biological patterns from large-scale metagenomic data. Qualifications: Applicants who meet the following requirements will be considered for the positions: ● A Ph.D. with less than 5 years of postdoctoral experience ● Ph.D. in Statistics/Biostatistics, Bioinformatics, Computer Science, or other relevant ● Extensive experience/training in Machine Learning, Statistics, Data structures, and Algorithms. ● Programming skills in Python, C/C++, GO, Rust, or equivalent. ● Strong oral and written communications skills ● Experience in genomics analysis Prior experience in at least one of the following computational areas is required: ● Deep Learning applied to protein science ● Probabilistic graphical model ● Statistical tool development ● Implementation of algorithms in a big data environment, especially high-performance computing clusters 申请方式： Applicants should send a cover letter, curriculum vitae, a statement of research interests, and contact information for three references (names and e-mail addresses) to Dr. Xiaofang Jiang (xiaofang@xiaofangjiang.com) using the following email subject: “PostDoc applicant - FirstName, LastName”. |
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