This job is archived
(Archived) Post-doctoral Scientist Bioinformatics
Job Description
We are seeking a talented post-doctoral bioinformatics scientist with experience in data management, analysis and interpretation of ‘omics data from mammalian and bacterial sources. This scientist will be part of a multi-disciplinary team working with diverse models and biological systems for target discovery, validation and product development. The successful candidate must have the ability to work in a matrixed team environment and have the ability to communicate complex data to non-bioinformatics experts. Experience working in a high-performance computing environment and managing all types of large, complex biological data is essential.
POSITION REQUIREMENTS AND RESPONSIBILITIES:
- Expertise in analyzing large datasets generated from DNA, RNA and protein sequences. Specifically, experience with next generation sequence assembly of DNA and RNA, mapping and analysis software, genotyping algorithms and variant detection, CNV analysis, systems biology and pathway analysis.
- Maintain up-to-date developments in algorithms for analysis of next-generation sequencing and applications of sequencing or collection of big data into health solutions
- Ability to conduct hypothesis-based research in partnership with a principal investigator at Zoetis and/or in collaboration with academia.
- Experience with systems biology approaches to elucidate complex physiological processes leading to health outcomes in animals
- Critical thinking and excellent communication and presentation skills are essential
- Experience with high density SNP data handling and analysis and genome wide association study knowledge are a plus.
EDUCATION AND EXPERIENCE:
- Educational background: PhD (Bioinformatics, Genomics, Animal Genetics, Veterinary Medicine or related field).
- Experience in data management, analysis and interpretation of omics data from mammalian sources. Self-starter, able to prioritize work, and work efficiently with minimal supervision
- Excellent verbal and written communication skills; ability to design, interpret, and present complex scientific data in a team environment is required
- Familiarity with various programming languages and software packages including:
- R, LINUX, Phyton, CLC Genomics Workbench and Ingenuity pathway analysis (IPA) is desired.