Computational PhD Intern, Clinical Science - Summer 2020 at Tempus
Passionate about precision medicine and advancing the healthcare industry?
Recent advancements in underlying technology have finally made it possible for AI to impact clinical care in a meaningful way. Tempus' proprietary platform connects an entire ecosystem of real-world evidence to deliver real-time, actionable insights to physicians, providing critical information about the right treatments for the right patients, at the right time.
At a summer at Tempus, you will:
- Apply skills and knowledge learned in the classroom to on-the-job experiences
- Comprehensive, value-added project(s)
- Have access to senior leadership and be involved in decision-making
- Work in teams and with colleagues in a professional environment
- Develop technical skills specific to your major
- Provides opportunities for professional development by building relationships and learning about other parts of the business
- End of summer presentation to the local management team
Duration and Timing
Tempus summer associates will spend ten weeks working in our Chicago headquarters. The program will commence in May/June and run through mid-August.
- Candidates must be enrolled in a post-grad degree program, preferably a doctoral program in Human Genetics, Cancer Genetics or Biological Sciences or a relevant quantitative discipline (eg bioinformatics, computational biology, statistical genetics, etc)
- Proficient in a scripting language, preferably R or Python
- Previous experience working with large NGS data sets and producing robust, well-annotated and reproducible analysis code
- Familiarity with human mutation databases, genome browsers and HGVS nomenclature
- Oncology experience strongly preferred
- Demonstrated attention to detail, excellent communication and writing skills
- Perform rigorous quantitative analysis of high dimensional molecular and clinical data
- Utilize a variety of computational tools to analyze sequencing variants from NGS data
- Help develop and validate novel computational tool(s) for clinical genomics platform
- Work independently and with other teammates in an interdisciplinary setting
- Effectively communicate project updates and key findings in weekly progress meetings
- End of summer presentation to clinical science leadership and other relevant teams
Proposed Project Description:
At Tempus, we have amassed the world’s largest library of clinical and molecular data and are committed to generating data-driven solutions to improve patient care. In this project, we aim to leverage and integrate our rich repository of DNA and RNA-seq data from our clinical oncology genomics platform in order to refine splice variant prediction and prioritization. Specifically, this project aims to detect splicing variants at natural and cryptic splice sites in DNA sequencing data from tumors using well-established and novel in silico splice variant prediction algorithms. Splice variants will be validated using in-house RNA-Seq data and compared against published pan-cancer databases of splice variants. Follow-up analyses will assess the impact of novel validated splice variants on variant classification for clinical reporting purposes as well identify novel candidates for potential biomarker discovery.