美國西奈山伊坎醫(yī)學院（ISMMS）2023年招聘博士后（空間生物學）
西奈山伊坎醫(yī)學院是紐約市的一所私立醫(yī)學院，是由西奈山醫(yī)院建立起來的，其主樓由著名建筑設(shè)計師I.M.Pei設(shè)計。該院在2022《美國新聞與世界報道》的醫(yī)學院中研究排名17，基礎(chǔ)醫(yī)療排名69。
Postdoctoral Fellow in Spatial Biology
Employer
YuanLab
Location
New York City, New York (US)
Salary
competitive salary with health and housing benefits
Closing date
Jan 11, 2024
Discipline
Life Sciences, Computational Biology, Genomics, Neuroscience, Physical Sciences, Computer Sciences, Statistics, Health Sciences
Position Type
Full Time
Job Type
Postdoc, Postdoc Fellowship, Research Scientist
Organization Type
Academia
A highly motivated postdoctoral fellow is recruited to conduct computational biology research in the field of spatial biology at the Department of Genetics and Genomic Sciences at Icahn School of Medicine at Mount Sinai (ISMMS). ISMMS is an international leader in medical and scientific training, biomedical research, and patient care. At ISMMS, world-class data scientists and clinicians work closely together toward precision medicine. The postdoc will join a leading spatial biology lab directed by Dr. Guo-Cheng Yuan. Previous work from this lab has produced widely recognized tools for spatial transcriptomics analysis, such as Giotto, HMRF, and spatialDWLS, and contributed to systems-level understanding of the gene regulatory mechanisms in development and multiple diseases. The postdoc will play a critical role in a newly funded NIH BRAIN Initiative project to develop computational tools for analyzing, harmonizing, and integrating the large amount of spatial transcriptomics and multi-omic datasets generated by the BRAIN Initiative, especially its cell atlas network component (BICAN), and in doing so enhances the internationally collaborative effort towards building a comprehensive, spatial-resolved human brain atlas. In addition, the postdoc will also have the opportunity to collaborate with the experts at ISMMS to use spatial biology as a tool to study the mechanisms underlying Alzheimer’s, bipolar, and other neuropsychiatric diseases.
The candidate should hold a PhD degree in a quantitative field. He/she should have strong analytical and programming skills, prior experience in analyzing genomic data (broadly defined), and demonstrated productivity through first-author peer-reviewed publications (including preprints). Experimentally trained candidates with a solid neurobiology background and sufficient statistical/programming skills are also encouraged to apply. Knowledge in spatial transcriptomics is desirable but not required. The candidate is expected to work well both independently and collaboratively.
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