Postdoctoral Research Associate - Computational Sciences

Position Responsibilities:

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.

• 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.

Minimum Education and/or Training:

• Ph.D. degree or equivalent in Bioinformatics, Molecular Biology, Biochemistry, Computer Science, or related field

Special Skills, Knowledge, and Abilities:

Required:

• 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.

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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.

Preferred:

• Experience with applied high-throughput sequencing analysis methods, including but not limited to alignment, coverage quantification, differential coverage statistics, and multi-omic integration

About the lab and St. Jude:

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.

TheAbraham 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 ofComputational Biologyprovides 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.Take the first step to joining our team by applying now!

Relevant Papers:

Adetunji MO, Abraham BJ. SEAseq: a portable and cloud-based chromatin occupancy analysis suite. BMC Bioinformatics. 2022 Feb 23; PMID: 35193506.

Hnisz D, Abraham BJ, Lee TI, Lau A, Saint-Andre 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

Lv J, Maher KA, Dong L, Valentine V, Staller S, Veluchamy A, Tian L, Kim Y, Ju B, Valentine M, Easton J, Pounds SB, Burden S, Abraham BJ. 3D-super-enhancers are condensate-associated cis-regulatory communities. Nucleic Acids Research. 2026 Feb 24;54(5):gkag191.doi: 10.1093/nar/gkag191. PMID: 41797539 PMCID: PMC12968393

Prutsch N, He S, Berezovskaya A, Durbin AD, Dharia NV, Maher KA, Matthews JD, Hare L, Turner SD, Stegmaier K, Kenner L, Merkel O, Look AT, Abraham BJ, Zimmerman MW. STAT3 couples activated tyrosine kinase signaling to the oncogenic core transcriptional regulatory circuitry of anaplastic large cell lymphoma. Cell Rep Med. 2024 Mar 19;5(3):101472. doi: 10.1016/j.xcrm.2024.101472. PMID: 38508140

Shendy NAM, Bikowitz M, Sigua LH, Zhang Y, Mercier A, Khashana Y, Nance S, Liu Q, Delahunty IM, Robinson S, Goel V, Rees MG, Ronan MA, Wang T, Kocak M, Roth JA, Wang Y, Freeman BB, Orr BA, Abraham BJ, Roussel MF, Schonbrunn E, Qi J, Durbin AD. Group 3 medulloblastoma transcriptional networks collapse under domain specific EP300/CBP inhibition. Nat Commun. 2024 Apr 25;15(1):3483. doi: 10.1038/s41467-024-47102-0. PubMed PMID: 38664416; PubMed Central PMCID: PMC11045757

Weichert-Leahey N, Zimmerman MW, Berezovskaya A, Look AT, Abraham BJ. Accurate Measurement of Cell Number-Normalized Differential Gene Expression in Cells Treated With Retinoic Acid. Bio Protoc. 2024 Nov 5;14(21):e5106. doi: 10.21769/BioProtoc.5106. eCollection 2024 Nov 5. PMID: 39525967; PMCID: PMC11543784

Zimmerman MW, Durbin AD, He S, Oppel F, Shi H, Tao T, Li Z, Berezovskaya A, Liu Y, Zhang J, Young RA, Abraham BJ, Look AT. Retinoic acid rewires the adrenergic core regulatory circuitry of childhood neuroblastoma. Science Advances. 2021 Oct 22; PMID: 34669465.

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