Job Description

The position of Postdoctoral Fellow (PDF) in computational cancer genomics is immediately available at The Cancer Science Institute of Singapore (The National University of Singapore). This PDF will lead a newly funded project in the laboratory of Dr. Jason Pitt that will explore how germline genetics and cell-of-origin contribute to genomic instability (GI) in cancer (see Pitt et al., 2018, Nat Comms; Pitt et al., 2018, Cancer Cell; Wang & Pitt et al., 2019, Int J Cancer). The acquisition of GI by malignant cells is critical to cancer development and progression. However, the magnitude and type of GI can vary widely across patients and cancer types. Delineating the underlying sources of GI will help identify novel therapeutic biomarkers (Pitt, Hoppe, & Jeyasekharan; PCT/SG2021/050105). The PDF will build upon our recently developed computational framework to derive dozens of GI scores and copy number signatures from tens of thousands of malignant samples. Using a multi-omic approach, these scores will be associated with clinical, genomic, and cell-type specific features. Candidate genes/variants will be investigated experimentally using CRISPR-mediated isogenic cell lines.

ROLES AND RESPONSIBILITIES

• Processing and management of public genomic data (WES, RNAseq, SNP array, etc.)
• Develop methods to estimate CN-based GI scores and signatures
• Use innovative approaches to associate inherited variation with GI patterns
• Determine the relationship between GI patterns and phenotypic features
• Lead manuscript writing and software documentation
• This position is for 2-3 years with the possibility of extension

PREFERENCES

• Familiarity with copy number and mutation signature analysis
• Experience using Amazon Web Services or high-performance computing
• Proficiency with Unix-based systems
• Experience with collaborative software development via github/gitlab

Qualifications

• PhD in human genetics, genomics, bioinformatics, or related fields
• Firm understanding of human genetics and association studies
• Experience analyzing cancer genomics data
• Strong Python and/or R programming skills
• Penchant for statistical reasoning
• Strong publication record
• Excellent written and spoken English