The department of Computational Biology is seeking a highly motivated scientist to join our Clinical Cancer Genomics team. As a clinical genome analyst, you will analyze and classify somatic and germline genetic alterations in pediatric cancer patients ascertained from whole-genome, whole-exome and transcriptome sequencing and present findings to pathologists, oncologists, and genetic counselors. This scientist will work closely with our bioinformatics pipeline and visualization teams to explore novel analysis approaches that aid molecular classification and clinical reporting, contribute ideas to automate and improve existing analysis methods, and assist in preparing and submitting manuscripts. The successful candidate will also have opportunities to participate in research projects to analyze the pediatric cancer genome and epigenome.
Our ideal candidate has a deep understanding of cancer biology and expertise in genomic and/or transcriptomic data analysis either through NGS or molecular pathology approaches. Prior experience within in a clinical environment and experience in clinical test development are highly desirable.
Recognized as a world leader in mapping the genetic landscape of pediatric cancers, the St. Jude department of Computational Biology has developed state-of-art computational infrastructure, well-established analytical pipelines, and deep genomic analysis expertise with a track record of high-impact publications in top-tier biomedical journals such as Nature, NEJM, JAMA, Nature Genetics and Nature Methods. The department provides a highly interactive environment with collaborative opportunities across basic and clinical departments, access to high performance computing clusters, cloud computing environment, innovative visualization tools, highly automated analytical pipelines and mentorship from faculty scientists with deep experience in data analysis, data management and delivery of high-quality results for highly competitive projects. This position is located in Memphis, TN, and relocation assistance is available.
PhD in Molecular Biology, Biochemistry, Computer Science, Bioinformatics or related field required. Prior experience must include research related to bioinformatics (such as analysis of DNA and RNA sequence data, microarray, SNPs, proteomics data, or biological pathways; development of algorithms, statistical methods, or scientific software).
If PhD training did not include bioinformatics research, will require a minimum of two (2) years of pre- or postdoctoral research experience in Computational Biology or Bioinformatics.
Experience with programming languages such as Perl, C, Python, Java, or R required.
Job Preferences: PhD in a field directly related to cancer biology with a strong desire to work in a clinical environment AND experience with programming languages.
Candidates at varying levels of their career will be considered.
PhD in Molecular Biology, Biochemistry, Computer Science, Bioinformatics or related field required.
PhD in a field directly related to cancer biology with a strong desire to work in a clinical environment preferred.