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The Abraham Lab at St. Jude Children’s Research Hospital seeks a Postdoctoral Research Associate to study gene regulation, chromatin, and genome organization in pediatric cancers.
This grant-funded role emphasizes computational biology within an inter-disciplinary team, offering opportunities to develop new methods and contribute to high-impact publications. Ideal candidates will hold a PhD in a quantitative field, have coding experience, and a track record in chromatin or expression analysis.
The Abraham Lab at St. Jude is seeking a Postdoctoral Research Associate to study gene dysregulation, chromatin composition, and genome organization in pediatric cancers.
This grant-funded position is part of an inter-institutional, interdisciplinary effort to deconvolve the roles of chromatin-modifying enzymes and complexes in cancer-driving gene regulation genome-wide. These proteins represent emerging drug targets in multiple pediatric solid tumors. Interdisciplinary collaboration with chemists and molecular oncologists, specifically the Adam Durbin, Lily Guenther, and Jun Qi (DFCI) labs, will be key components of the work.
The initial appointment will be for 1-2 years and can be renewed for up to a total of 5 years, depending on the candidate's goals and qualifications.
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 impact the future care of pediatric cancer patients. As a Postdoctoral Research Associate, your responsibilities include analyzing data generated from a variety of second- and third-generation sequencing applications that interrogate gene regulatory biology in health and disease.
The Abraham lab studies gene expression-regulation mechanisms. We are recruiting computational biologists to collaboratively develop software approaches to analyze high-throughput sequencing (-omic) data. We build analytical software pipelines to find answers to biological questions about gene regulation in genome-wide datasets, usually from applied sequencing experiments like CUT&RUN, RNA-Seq (bulk, single-cell, and spatial), and HiChIP, as well as single-cell omic experiments. 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 characterize the specific core regulatory circuitries driving disease-relevant cells and seek to understand how mutations in the non-coding DNA of such cells can drive disease, including cancers, through gene misregulation.
The Durbin lab uses cutting-edge genome-scale technologies to identify and target the fundamental mechanisms controlling high risk pediatric solid tumors. Our lab bridges epigenetics and transcriptional biology with chemical biology, animal modeling of human cancer and genome editing to identify and develop new methods to target key cancer drivers in challenging to treat pediatric solid tumors. We have identified several key cancer drivers and compounds in high-risk pediatric solid tumors in which there are limited options for therapy, such as neuroblastoma. We focus on understanding several themes: 1) how the epigenetically controlled transcriptional state of the cancer cell contributes to its malignant properties; 2) dissecting transcription factor control of malignant properties; and 3) Using next-generation chemical and cell-based therapies to target these processes.
The successful candidate will become a fundamental component of a multidisciplinary, inter-institutional team assembled to study how gene expression regulation meaningfully differs between normal and pediatric cancer cells and might be productively targetable. The successful candidate will lead research projects within the laboratory with increasing independence in daily operation.
Ideal candidates will have experience building, tailoring, and deploying analysis pipelines using widely available genomic analysis toolkits (e.g. bedtools, samtools, HiCPro, Tuxedo tools), as well as experience managing large numbers of datasets and on a well-supported high-performance compute cluster. 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 the 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, a 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. First-author, high-profile publications are required to share this element of discovery.
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