Postdoctoral Research Associate - Computational Sciences

St. Jude Children's Research Hospital • Memphis, TN

1d • Onsite

About The Position

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 successful candidate will lead computationally focused scientific research projects with increasing independence over time, collaborate on project and analysis design under the guidance of multiple invested PIs, set personal task-level priorities across multiple interconnected projects, develop new computational methods, adhere to field and lab standards for data analysis, identify, process, organize, interpret, review, and report relevant data, direct data collection, and present research to colleagues within and outside the institution. They will also draft a complex manuscript with minimal supervision, as required, and perform other duties as assigned to meet the goals and objectives of the department and institution. The candidate will maintain regular and predictable attendance, especially in-person attendance at meetings and relevant presentations. 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. 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.

Requirements

• Candidates must hold a doctoral degree (PhD, MD, or equivalent).
• Applicants with a PhD in a quantitative and biologically oriented field (computational biology, bioinformatics, systems biology, genetics/genomics, statistics, mathematics, computer science, or related fields) are especially encouraged to apply.
• Strong candidates from a primarily wet-lab or clinical background who wish to develop sophisticated quantitative skills will also be considered.
• Such applications would be strengthened by displaying coding experience.
• Successful candidates will have a track record of scientific productivity, e.g., a first author paper, or a demonstrable contribution to a large project.
• Experience in chromatin and expression analysis technologies is desired.
• 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.
• First-author, high-profile publications are required to share this element of discovery.

Nice To Haves

• Experience with applied high-throughput sequencing analysis methods, including but not limited to alignment, coverage quantification, differential coverage statistics, and multi-omic integration
• Additional experience in the fundamental understanding of gene expression mechanisms (e.g. transcription factors, enhancers, genome structure, and transcriptional condensates)
• Experience building succinct, clear figures using R are preferred.

Responsibilities

• Lead computationally focused scientific research projects with increasing independence over time.
• Collaborate on project and analysis design under the guidance of multiple invested PIs.
• Set personal task-level priorities across multiple interconnected projects.
• Develop new computational methods.
• Adhere to field and lab standards for data analysis.
• Identify, process, organize, interpret, review, and report relevant data.
• Direct data collection.
• Present research to colleagues within and outside the institution; draft a complex manuscript with minimal supervision, as required.
• Perform other duties as assigned to meet the goals and objectives of the department and institution.
• Maintains regular and predictable attendance, especially in-person attendance at meetings and relevant presentations.

What This Job Offers

• Job Type: Full-time
• Career Level: Entry Level
• Education Level: Ph.D. or professional degree