Postdoctoral Research Associate - Computational Biology

Overview

The Abraham Lab is seeking a Postdoctoral Research Associate to study the roles of gene dysregulation 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 in genome-wide gene regulation. These enzymes represent emerging drug targets in pediatric solid tumors and collaboration with chemists and molecular oncologists will be key components of the work.

• Lead computationally focused scientific research projects with increasing independence over time.
• Collaborate on project and analysis design guided by their PI.
• 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.
• Maintain regular and predictable attendance.

• Ph.D. degree or equivalent in Bioinformatics, Molecular Biology, Biochemistry, Computer Science, or related field
• Special Skills, Knowledge, and Abilities:

• Candidates must hold a doctoral degree (PhD, MD, or equivalent). Applicants with a PhD in a quantitative field (computational biology, bioinformatics, systems biology, genetics/genomics, statistics, mathematics, computer science, or related fields) are encouraged to apply.
• Strong candidates from a primarily wet-lab or clinical background who wish to develop sophisticated quantitative skills will also be considered.
• 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.

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.

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

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, 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 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…