Zoetis is seeking a Computational Biologist specializing in the analysis and integration of complex datasets generated from multi-omics and in-vitro data sets across several diverse biological systems. The role will require a good understanding of biology as well as the relevant data types to allow the development of analysis strategies and pipelines. The role will report into our Bioinformatics Team in VMRD Genetics but collaborate widely with scientists across all of Zoetis research groups. Excellent communication skills will be necessary to enable work with multi-disciplinary teams. The successful candidate will demonstrate an enthusiasm to work, collaborate, and communicate with both computational and experimental colleagues.
- Develop, troubleshoot, and utilize statistical and analytical methodologies for the analysis of internal and external datasets.
- Develop, apply, enhance, and standardize current and new computational pipelines for multi-omics high-throughput datasets including NGS, quantitative proteomics, and in-vitro biology data.
- Design, guide, and conduct statistically rigorous data analyses to support research projects and discover biological insights.
- Have a strong attention to detail, organizational skills, the ability to multitask, and effective interpersonal and communication skills.
- Document analytical results in regulated systems and technical reports.
- Develop and apply computational tools for data sharing and visualization.
- Maintain awareness of emerging methods in computational biology and applications for novel omics technologies.
EDUCATION and EXPERIENCE
- Ph.D. in computational biology, bioinformatics, computer science, or a related technical field with 0-5 years of industrial experience in the analysis of in-vitro biology and omics datasets.
- Working knowledge of molecular and cell biology required.
- Strong quantitative reasoning and statistical analysis skills with ability to apply them to relevant scientific projects and interpret of the results.
- Candidates should be proficient in at least one programming language (such as Python, BASH, C, C++, R)
- Strong oral and written communication skills to collaborate with computational and experimental scientists located at multiple sites.
- Well-cited journal publications and presentations.
- Strong background in ‘omics pipeline development.
- Experience with high density SNP data, such as genome wide association studies (GWAS) and genomic selection is a plus
- Demonstrated experience applying computational and statistical approaches to deliver analysis ready data e.g. multivariate and machine learning approaches.
- Deep understanding of the statistical methods commonly used in omics analyses.
- Experience in an analysis of proteomics and metabolomics data.
- Demonstrated ability to effectively interface with biologists to communicate and discuss results.
- Exceptional documentation and communication skills.
- Self-motivated and highly effective in a team-based environment.