Senior Bioinformatics Research Scientist - Northcott Lab in the Center of Excellence in Neuro-Oncology Sciences (CENOS)

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

45d

About The Position

The Northcott Lab in the Center of Excellence in Neuro-Oncology Sciences (CENOS) at St. Jude Children’s Research Hospital is seeking a highly motivated Senior Bioinformatics Research Scientist. CENOS is a collaborative research environment that aims to drive discoveries needed to improve outcomes for children with brain tumors. Through application of cutting-edge molecular profiling to unprecedented patient cohorts and innovative model systems, CENOS members are rapidly translating laboratory findings into new treatments. Genome-wide studies of diverse pediatric brain tumor entities have identified novel mutations, defined molecular subgroups, and opened new avenues of basic, translational, and clinical investigation. The Senior Bioinformatics Research Scientist performs data analysis, data visualization, statistical analysis, experimental design, database development, mathematical modeling, and novel method development. Provides bioinformatics analysis for investigators and communicates analytical process and results. The successful candidate will contribute to discovery-driven computational studies of unprecedented multi-omic datasets obtained from children with malignant brain cancer, including single-cell, spatial, and liquid biopsy profiles. The candidate will work closely with other bioinformatics personnel within CENOS to play an integral role in exciting collaborations, both within St. Jude and with prominent external collaborators. A deep understanding of cancer genomics, human genetics, transcriptomics, or epigenetics, strong problem-solving skills, attention to detail, and critical thinking are essential for this position. The successful recruit must have the capacity to execute proficient computational analyses and troubleshooting independently, communicate effectively with the PI and collaborators, and thrive in a highly collaborative team environment. The ideal candidate should have: A PhD in bioinformatics, computational biology, data science or related field. Experience analyzing the following platforms: Single-cell/nucleus RNA-seq, spatial transcriptomics, RNA-seq, ATAC-seq, ChIP-seq/CUT&RUN, and DNA methylation A strong CV that includes publications involving cancer genomics, epigenomics, single-cell, spatial ‘omics, machine learning, and artificial intelligence. Experience in analyzing, interpreting, and visualizing human genomics datasets generated by high-throughput sequencing platforms including short- (Illumina) and long-read- (e.g. PacBio and Oxford Nanopore) whole-genome sequencing. Proficiency in relevant programming languages such as R and Python, preferably in a High-Performance Computing (HPC) environment. Proficiency in tools for ensuring reproducibility of pipelines, such as workflow management systems (e.g., nextflow or snakemake), and version control (e.g., git). Extensive expertise in data integration and harmonization. Proven problem-solving skills and collaborative nature in fast-paced environment. Excellent communication and presentation skills.

Requirements

Bachelor's degree in bioinformatics, cheminformatics, statistics/computer science (with a background in biological sciences or chemistry) or related field.
Minimum Requirement: Bachelor's degree with 7+ years of relevant post-degree work in bioinformatics, cheminformatics, statistics/computer science (with a background in biological sciences or chemistry).
Experience Exception: Master's degree with 5+ years of relevant post-degree experience (OR) PhD with 2+ years of relevant post-degree experience.
Significant experience in at least one programming or scripting language and at least one statistical package, with R preferred.

Nice To Haves

A PhD in bioinformatics, computational biology, data science or related field.
Experience analyzing the following platforms: Single-cell/nucleus RNA-seq, spatial transcriptomics, RNA-seq, ATAC-seq, ChIP-seq/CUT&RUN, and DNA methylation
A strong CV that includes publications involving cancer genomics, epigenomics, single-cell, spatial ‘omics, machine learning, and artificial intelligence.
Experience in analyzing, interpreting, and visualizing human genomics datasets generated by high-throughput sequencing platforms including short- (Illumina) and long-read- (e.g. PacBio and Oxford Nanopore) whole-genome sequencing.
Proficiency in relevant programming languages such as R and Python, preferably in a High-Performance Computing (HPC) environment.
Proficiency in tools for ensuring reproducibility of pipelines, such as workflow management systems (e.g., nextflow or snakemake), and version control (e.g., git).
Extensive expertise in data integration and harmonization.
Proven problem-solving skills and collaborative nature in fast-paced environment.
Excellent communication and presentation skills.

Responsibilities

Provide research support and deliver high-quality results by formulating an efficient analytical approach with the available data.
Deliver data files, and document the analytical process.
May participate in manuscript preparation at project's conclusion.
Assist with establishing and documenting protocols or best practices for common research tasks, and in the formulation of analytical plans that use the best approach to address challenging data analysis questions.
Assist in the evaluation and testing of new methods and technologies.
Contribute ideas to automate or improve existing analysis methods.
Implement the improvement or work with others to do so.
Participate in the department's developmental projects and interdepartmental team projects.
Perform other duties as assigned to meet the goals and objectives of the department and institution.
Maintains regular and predictable attendance.