Research Scientist I, Bioinformatics

94404, Foster City
Oct 10, 2018
Required Education
Position Type
Full time

Research Scientist I, Bioinformatics


For Current Gilead Employees and Contractors:

Please log onto your Internal Career Site to apply for this job.


Job Description

We are looking for a highly talented and motivated bioinformatics scientist to join our research bioinformatics team in Biology Core Support group. The successful candidate will provide bioinformatics data analysis supports for our oncology programs from target identification and evaluation to biomarker discovery and validation. The successful candidate will work closely with research scientists to develop and implement rigorous statistical and bioinformatics methods to analyze high-throughput molecular data, integrate large scale datasets, interpret and present the analysis results.


The main responsibilities of the successful candidate will include:

• Perform quality control analysis of high-through-put molecular data sets (e.g., microarray, RNA-Seq, WES, WGS, Chip-Seq, NanoString, multiplex qPCR, TCR-Seq, etc).

• Identify differential gene expression and pathway activation in preclinical models and clinical data sets.

• Apply statistical algorithms and create bioinformatics tools to analyze large scale biological data sets from publicly available, commercial, and proprietary genomic databases to identify the pharmacodynamic, predictive, and prognostic biomarkers.

• Mine scientific literatures to discover gene signatures and pathways related to the drug targets. 


Required Knowledge, Experience and Skills:

• A PhD degree in bioinformatics, computational biology, genomics, or closely related fields.

• Prior working experience in biopharmaceutical industry is preferred.

• Strong programming and scripting abilities in languages, such as R, Perl, Python.

• Familiar with Linux/Unix systems.

• Hands-on experience with open-source bioinformatics tools and packages to analyze microarray (e.g., Affymetrix GeneChip, Illumina BeadChip) and next-generation sequencing data (e.g., RNA-Seq, DNA-Seq, Chip-Seq). Solid understanding of the statistical principles employed in these tools.

• Familiar with public databases, such as TCGA, GTEx, CCLE, ICGC

• Strong knowledge of statistics and machine learning algorithms, such as probability theory, sample size and statistical power, univariate and multi-variate analysis, unsupervised and supervised analysis, regression analysis.

• An understanding of the relevant biology concepts in the analyzed data sets.

• Able to work independently and to handle multiple projects in a fast-paced working environment.

• Strong oral/written communication and data presentation skills.


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For Current Gilead Employees and Contractors:

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