Join our Clinical Cancer Genomics team where your biological expertise and coding skills will directly impact the care of pediatric cancer patients. As a clinical genome analyst, you will curate and mine whole-genome, whole-exome and transcriptome sequencing data and also create and validate new computational methods to detect and classify somatic and germline genetic alterations in pediatric cancer patients. These methods will uncover genetic predispositions to cancer and allow us to match patients to targeted therapies and clinical trials. Our team has a clear goal: to integrate clinical genomics into the continuum of care and improve patient outcomes.
By understanding both computational methods and the underlying biology, you will form the vital connection between laboratory scientists and clinicians necessary to make precision oncology a reality. Our clinical genome analysts are part of a multidisciplinary team and will work closely with pathologists, oncologists and genetic counselors. You also 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. The analyst will also have the opportunity to participate in research projects and lead and assist in preparing and submitting manuscripts.
The 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, Blood Advances, Nature Genetics and Nature Communications. St. Jude Cloud is the world’s largest public repository of pediatric cancer genomics data on a cloud computing platform designed to be fast and easy to use. The department provides 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.
Take the first step to join our team by applying now!
PhD in Molecular Biology, Biochemistry, Computer Science, Bioinformatics or a field directly related to cancer biology is required.
We will consider PhD graduates with strong bioinformatics/computational biology skills.
If PhD training did not include bioinformatics, will require a minimum of two (2) years of pre- or postdoctoral research utilizing computational biology, bioinformatics and NGS analysis methods.
Experience with programming languages required.