Summary/Contribution of Position:
The Computational Biologist will work as a core member of the R&D team leading the analytical aspects of product development with in-depth knowledge of a broad range of computational analytical tools and strategies to analyze multi-omic datasets. You will perform and/or supervise the performance of in silico experiments to support RNA research, Epigenetic research, Clinical applications, and other related service as required.
Essential Duties and Responsibilities:
- Develop advanced computational methods to enhance research and discovery on epigenomic, transcriptomic and genomic platforms.
- Enhance bioinformatic analysis of diverse NGS and non-NGS datasets, including RNA-seq, WGBS, Targeted sequencing, MicroArray etc.
- Develop innovative, robust, computational and statistics methods that can be applied in research and clinical settings.
- Provide intellectual and technical excellence to guide new discovery strategies. Design, perform, troubleshoot, and interpret experiments.
- Present project updates, data analysis at technical and commercial meetings.
- Identify, develop, and manage collaborations and partnerships.
Education and Experience:
- PhD or master’s in Bioinformatics, Computational Biology, Applied Mathematics, Statistics, Epidemiology, Biological sciences, Cancer biology, Genetics, Genomics, Computer science, or a related discipline with a strong record of publications/patents is required.
- Experience in the analysis of large next-generation sequencing date sets and microarray data.
- Hands-on experience on working with various public and proprietary data repositories, such as TCGA, GTEx, dbSNP, Ensembl, UCSC genome browser.
- Experience with manipulation and innovative analysis (e.g. novel algorithm development) of large biological and/or epidemiology data sets.
- Experience with statistics and/or machine learning.
- Extensive experience in bio-computational programming, scripting, querying or statistical analysis languages such as python or R, as well as Linux OS for high performance computing.
- Familiarity with Amazon Web Services EC2 and S3.
- Biological research experience.