Postdoctoral Research Position in Single Cell Genomics
One or two postdoctoral positions in computational biology focused on single cell genomics is available at the Guo-Cheng Yuan Lab in the Department of Biostatistics and Computational Biology at Dana-Farber Cancer Institute / Harvard T.H. Chan School of Public Health.
The goal of the Yuan Lab is to develop computational approaches to analyze and integrate genomic data with the aim to elucidate systems-level gene regulatory mechanisms in development and disease. Current projects include single-cell analysis, genome-wide chromatin state characterization, inference of gene regulatory networks, and functional characterization of genetic variants. Detailed description of our research can be found at our group website: http://bcb.dfci.harvard.edu/~gcyuan.
The candidate(s) will develop computational methods for analyzing single-cell transcriptomic and mass cytometry data, with the goals to characterize cellular states and identify rare cell-types, to model the dynamic changes associated with cell-state changes, to investigate the regulatory mechanism at gene expression variation, and to apply this knowledge to stem cell and cancer biology. The candidate will have the opportunity to closely interact with basic biologists and clinical investigators at the Dana-Farber Cancer Institute and Boston Children’s Hospital.
The successful applicant(s) should hold a doctoral degree or equivalent qualification in computational biology, (bio)statistics, computer science, or a similar field. Candidates holding a degree in biological / medical science are also welcome to apply if they have demonstrated experience in computational or statistical work.
Strong programming (in Python, R, Matlab, or C/C++) and communication skills are required. Previous experience in analysis, interpretation, and integration of genomic, transcriptomic and epigenomic data is also required. Previous knowledge in single-cell biology is highly desired but not required.
Lead author in at least one publication in major peer-reviewed scientific journals.
Administrative questions regarding this position can be sent to Susan Luvisi at firstname.lastname@example.org.
Scientific questions regarding this position can be sent to Guo-Cheng Yuan at email@example.com.
Equal Opportunity Employer
We are an equal opportunity employer and all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability status, protected veteran status, or any other characteristic protected by law.
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