Postdoctoral positions in COMPUTATIONAL GENOMICS are available in Dr. Adam Siepel’s research group at the Simons Center for Quantitative Biology, Cold Spring Harbor Laboratory.
The Siepel Group specializes in the development of probabilistic models, algorithms for inference, prediction methods, and application of these methods in large-scale genomic data analysis. Of particular interest is research relevant to existing, NIH supported projects in (1) HUMAN POPULATION GENOMICS including demography inference using Bayesian coalescent-based methods, inference of natural selection on regulatory and other noncoding sequences, and prediction of fitness consequences for noncoding mutations; and (2) TRANSCRIPTIONAL REGULATION in mammals and Drosophila, including the estimation of rates and patterns of transcriptional elongation from GRO-seq data, prediction of transcription factor binding sites from DNase-seq data, and regulatory network inference based on joint patterns of transcription and binding in inducible systems.
RELEVANT RECENT PAPERS INCLUDE THE FOLLOWING:
Danko CG, Choate LA, Marks BA, Rice EJ, Zhong W, Chut T, et al. Dynamic evolution of regulatory element ensembles in primate CD4+ T-cells. Nat. Ecol. Evol. 2(3):537-548, 2018.
Huang Y-F, Gulko B, Siepel A. Fast, scalable prediction of deleterious noncoding variants from functional and population genomic data. Nat. Genet. 49(4):618–624, 2017.
Kuhlwilm M, Gronau I, Hubisz MJ, de Filippo C, Prado J, Kircher M, et al. Ancient gene flow from early modern humans into Eastern Neanderthals. Nature 530(7591):429–433, 2016.
Core LJ, Martins AL, Danko CG, Waters CT, Siepel A, Lis JT. Analysis of nascent RNA identifies a unified architecture of initiation regions at mammalian promoters and enhancers. Nat. Genet. 46(12):1311–1320, 2014.
Rasmussen MD, Hubisz MJ, Gronau I, Siepel A. Genome-wide inference of ancestral recombination graphs. PLOS Genet. 10(5):e1004342, 2014.