Post-Doctoral Research Associate Biology
Position Description
We are seeking a bioinformatician to analyze genome wide transcriptomic responses to stress in plants and microbes for functional genomic studies. The post doc will be involved in many exciting projects using newly assembled reference genomes of host plants and nitrogen-fixing symbiotic microbes. We are particularly interested in genes that can enhance tolerance to stress or toxic environments. Incorporation of evolutionary and/or ecological aspects and analyses into this research is highly encouraged. The research is essential to meet the DOE’s Biological and Environmental Research (BER) mission to use genome-enabled approaches to understand the relationship between soil biogeochemistry, nutrient cycling by plants, and the movement or transport of metals ions from soils into plant biomass. (https://www.energy.gov/science/ber/biological-and-environmental-research)
This position has a high level of interaction with an international and multicultural scientific community, including the Joint Genome Institute (JGI) and the Environmental Molecular Sciences Laboratory (EMSL), both DOE run facilities. The research will support two JGI funded community science awards (New Investigator and Functional Genomics).
Essential Duties and Responsibilities:
- Quantify gene expression changes in response to stress treatments such as heavy metals, temperature, drought.
- Assess the role of gene duplications on expression level.
- Identify candidate genes that provide greater tolerance to stress.
- Develop statistical pipelines to identify differentially expressed genes and co-expression networks.
- Integrate genome wide association study (GWAS) candidates with transcriptomics data to identify target genes for functional studies.
Required Knowledge, Skills, and Abilities:
- Requires a Ph.D. in bioinformatics or biology with focus on genomics, or computational biology, evolutionary genomics, plant genomics/agricultural genomics or related field.
- Experience mapping and analyzing RNA-seq data, including differential expression analysis (e.g. DeSEQ, edgeR).
- Ability to install and use bioinformatics software (i.e., samtools, BWA, GATK, plink) in a Linux framework.
- Proficient in one or more programming languages such as python or perl, and ability to write and modify scripts in R.
- A proven track record of experimental design, execution and data analysis as reflected in manuscript writing and successful publication in peer-reviewed journals.
- Demonstrated track record of poster presentations and/or oral presentations at scientific meetings.
Preferred Knowledge, Skills, and Abilities:
- Standard genome annotation software experience with genome assembly and annotation using RNA-seq data.
- Gene co-expression network analysis using WCGNA or other tools.
- Single gene alignment software and PCR primer design.