Bioinformatics Research Scientist

Memphis, TN

About St. Jude Children's Research Hospital

The World’s Most Dedicated Never Give Up

There’s a reason St. Jude Children’s Research Hospital is recognized as a great place to work. Because at our world-class pediatric research hospital, every one of our professionals shares our commitment to make a difference in the lives of the children we serve. There’s a unique bond when you’re part of a team that gives their all to advance the treatments and cures of pediatric catastrophic diseases. The result is a collaborative, positive environment where everyone, regardless of their role, receives the resources, support and encouragement to advance and grow their careers and be the force behind the cures.

Bioinformatics Research Scientist

We are seeking a talented, highly motivated Lead-Bioinformatics Analyst to facilitate and undertake next-generation sequencing (NGS) projects in the Department of Developmental Neurobiology (DNB). In this position, you will be a shared resource for research groups in DNB. You will have the opportunity to work with top scientists in the field, to work on novel and important research projects, and to learn and use cutting-edge technologies. The three main focus areas for this position are developing new approaches/innovation, experimental support for the labs, and training DNB team members. This is a great opportunity for establishing one’s bioinformatics career, gaining new skillsets, and making an impact in science.

 

The successful recruit must have a deep understanding of NGS technologies, strong communication, problem-solving skills, and critical thinking. Experience in NGS data analysis is preferred. Proficiency with a programming language such as Python and/or R is preferred along with familiarity with the Linux command line. Candidates with experience in coordinating NGS research projects, teaching, and collaborations will be preferred.

 

If you are passionate about genomics data, love science, and enjoy helping people, this is a great opportunity for you to grow and thrive. Apply now!

As a Lead-Bioinformatic Analyst, you are responsible for independent analysis of biomedical data produced from a variety of NGS technologies, including RNA-seq, ChIP-seq, ATAC-seq, WGS/WES, and single cell RNA-seq. You will develop bioinformatics pipelines or use contemporary, advanced software packages for conducting data analysis of complex biomedical datasets. Other responsibilities include:

  • Work closely with experimental researchers to understand analytical needs, provide technical consultation, design analytical approaches, generate/provide analysis results and reports, and perform requested custom analyses.
  • Independently design and perform statistical analysis of results and interpret results.
  • Manage projects and coordinate other efforts related to data analysis and infrastructure.
  • Design and prepare materials for training lab scientists on software usage, quality control metrics of NGS data, and data analysis techniques.
  • Contribute to the evaluation and recommendation of new software tools to meet the growing needs of the research community at St. Jude.
  • Minimum Requirement: Bachelor's degree with 6+ 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 4+ years of relevant post-degree experience (OR) PhD with no experience.
  • Experience in at least one programming or scripting language and at least one statistical package, with R preferred.
  • End user support and training experience is required.
  • Experience with open source software development preferred.
  • Experience in development of algorithms, statistical methods or scientific software preferred.
  • Experience in next-generation sequence analysis or imaging analysis is preferred.
  • Experience in working with high-throughput data sets in a highly competitive environment is preferred.
  • Experience in working in a team project is preferred.
  • Cross training in biological sciences (e.g. genomics, genetics, transcriptomics and epigenetics) preferred
  • Scripting experience using a statistics package such as R, S-Plus or SAS preferred.