Senior Computational Research Scientist

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

19h

About The Position

The Abraham Lab is seeking a Senior Computational Research Scientist to study the role of gene dysregulation and genome 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 impact the future care of pediatric cancer patients. As a Senior Computational Research Scientist, 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 Hi-ChIP, as well as single-cell omic experiments. Our interests center on enhancers, super-enhancers and core transcriptional regulatory circuits. 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. The successful candidate will operate as a superdoc-type contributor who leads 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), 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 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. We encourage first-author, high-profile publications to share this element of discovery.

Requirements

Bachelor's degree in Bioinformatics, Molecular Biology, Biochemistry, Computer Science, or related field.
Bachelor's degree and 7+ years of relevant experience.
Master's degree and 5+ years of relevant experience (OR) PhD with 2+ years of relevant experience.
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 further develop sophisticated quantitative skills will also be considered.
Such applications would be strengthened by displaying significant 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 strongly desired.

Nice To Haves

Master's degree or PhD strongly preferred.
Experience with applied high-throughput sequencing analysis methods, including but not limited to alignment, coverage quantification, differential coverage statistics, and multi-omic integration.
Experience building, tailoring, and deploying analysis pipelines using widely available genomic analysis toolkits (e.g. bedtools, samtools, HiCPro).
Experience managing large numbers of datasets.
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).
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, especially pertaining to regulatory circuitry controlling pediatric cancers.
Apply and integrate field-standard omics pipelines for similar technologies, e.g. ChIP-Seq/CUT&RUN/CUT&TAG, ATAC-seq, HiChIP/HiC, bulk/single-cell RNA-seq.
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, especially in-person attendance at meetings and relevant presentations.