St. Jude Children’s Research Hospital is seeking a Bioinformatics Research Scientist in Epigenetics Group in the Center for Applied Bioinformatics (CAB). CAB is a newly established center to provide centralized genomic and bioinformatic analytic services and collaborations for investigators (PIs) at St. Jude Children's Research Hospital. You will have the opportunity to work on diverse projects together with different PIs and contribute to pediatric cancer patient curation and survival, explore new methods, develop pipelines, in addition to the routine analysis tasks. We encourage you to be a first author on high profile publication with opportunities to cross-train and collaborate with the Transcriptomics and Genetics Groups in the CAB.
Good candidates will have experience building, optimizing analysis pipelines using available software or installing pipelines for high-throughput next generation sequence data analysis (such as ChIP-Seq, ATAC-Seq, RNA-Seq, Hi-C/HI-CHIP/CaptureC) under Linux/Unix environment. The successful candidate is expected to have good programming skills in Bash, Python and R, have an understanding of basic epigenetics gene regulation mechanisms (e.g. Histone Modification, Chromatin Accessibility, DNA Methylation, 3D Genome). Experience with deep learning or C++ or CWL is a plus.
St. Jude Children’s Research Hospital is seeking multiple Bioinformatics Research Scientists to study the role of genome and other nuclear organization in pediatric cancers. Recognized for state-of-the-art computational infrastructure, well-established analytical pipelines, and deep genomic analysis expertise, St. Jude offers a work environment where you will directly impact the care of pediatric cancer patients. As a Bioinformatics Research Scientist, your responsibilities include analyzing data generated from a variety of second- and third-generation sequencing applications that interrogate a broad range of human gene regulatory biology.
The Abraham lab studies gene expression-regulation mechanisms in healthy and diseased mammalian cells. We are recruiting computational biologists to collaboratively develop computational tools and frameworks to analyze high-throughput sequencing (-omics) data. We build analytical software pipelines to find answers to biological questions about gene regulation in big datasets, usually from applied sequencing experiments like ChIP-Seq, RNA-Seq, and Hi-ChIP. Our interests center on enhancers and super-enhancers. Specifically, we seek to understand how these regulatory elements establish gene expression programs in healthy cells, and how enhancers are altered by mutation, abused by mistargeting, and targetable with drugs in diseased cells. We focus on characterizing the core regulatory circuitries driving disease-relevant cells, and on understanding how mutations in the non-coding DNA of such cells can drive disease, including cancers, through gene misregulation.
The successful candidate will become a fundamental component of a multidisciplinary, inter-institutional team assembled to study how genome structures meaningfully differ between normal and pediatric cancer cells.
Ideal candidates will have experience building, tailoring, and deploying analysis pipelines using widely available genomic analysis toolkits (e.g. bedtools, samtools), as well as experience managing large numbers of datasets. The successful candidate will be tasked with collaborative research within and beyond the lab, so strong communication and interpersonal skills are essential. Additional experience in fundamental understanding of gene expression mechanisms (e.g. transcription factors, enhancers, genome structure, and transcriptional condensates), and experience building succinct, clear figures using R are preferred.
The department of Computational Biology provides access to high performance computing clusters, cloud computing environment, innovative visualization tools, highly automated analytical pipelines and mentorship from faculty scientists with experience in data analysis, data management and delivery of high-quality results for competitive projects. We encourage first author, high profile publications to share this element of discovery. Take the first step to join our team by applying now!
Abraham BJ, Hnisz D, Weintraub AS, Kwiatkowski N, Li CH, Li Z, Weichert-Leahey N, Rahman S, Liu Y, Etchin J, Li B, Shen S, Lee TI, Zhang J, Look AT, Mansour MR, Young RA. Small genomic insertions form enhancers that misregulate oncogenes. Nat Commun. 2017 Feb 9;8:14385. doi: 10.1038/ncomms14385. PubMed PMID: 28181482; PubMed Central PMCID: PMC5309821.
Hnisz D, Abraham BJ, Lee TI, Lau A, Saint-André V, Sigova AA, Hoke HA, Young RA. Super-enhancers in the control of cell identity and disease. Cell. 2013 Nov 7;155(4):934-47. doi: 10.1016/j.cell.2013.09.053. Epub 2013 Oct 10. PubMed PMID: 24119843; PubMed Central PMCID: PMC3841062.
Dowen JM, Fan ZP, Hnisz D, Ren G, Abraham BJ, Zhang LN, Weintraub AS, Schujiers J, Lee TI, Zhao K, Young RA. Control of cell identity genes occurs in insulated neighborhoods in mammalian chromosomes. Cell. 2014 Oct 9;159(2):374-387. doi: 10.1016/j.cell.2014.09.030. PubMed PMID: 25303531; PubMed Central PMCID: PMC4197132.