Two Postdoctoral scientists positions in Quantitative Biology are available in the laboratory of Dr. Ebrahimi. The qualified candidates will be working on projects related to viral/cancer immunity and evolution. The overall aims of the projects are to develop and apply multi-omic approaches to mine and deconvolute complex datasets including genomic, transcriptomic, and proteomic data from viruses, hosts, and tumors to: a) discover population-specific virus-host interaction mechanisms and identify underlying genetic and evolutionary sources; b) delineate gene expression profiles in cancer and investigate their association with germline/somatic mutations, viral status, and other clinical data.
Texas Biomed provides unique research and training opportunities for postdocs, including access to exceptional resources such as BSL4, SNPRC (Southwest National Primate Research Center), a vigorous infectious disease program on HIV, malaria, schistosomiasis, Ebola, Zika, hepatitis C and TB, and outstanding imaging, computational, and sequencing facilities. Texas Biomed faculty have adjunct appointments at two universities in San Antonio (UTSA and UTHSCSA), which provide a wide range of additional training and career development opportunities for postdocs at Texas Biomed.
- D. Ebrahimi et al., Genetic and Mechanistic basis for APOBEC3H alternative splicing, retrovirus restriction, and counteraction by HIV-1 protease. Nature Communications 2018, 9(1), 4137. PMCID: PMC6175962.
- H. Alinejad-Rokny et al. Source of CpG depletion in the HIV-1 genome. Molecular biology and Evolution 2016, 33(12), 3205. PMID: 27682824
- F. Anwar et al., Footprint of APOBEC3 on the genome of human retroelements. Journal of Virology 2013, 87(14), 8195. PMCID: PMC3700199
EDUCATION/EXPERIENCE/SKILLS: Required: Ph.D. in a quantitative science discipline such as bioinformatics, computer science, mathematics, statistics, physics, or engineering. Skills in working with large datasets and developing tools and algorithms for analysis of large datasets. Coding in one or more platforms, e.g. Python, R, Matlab. Passion for learning quantitative biology. Preferred: Ph.D. in quantitative biology or bioinformatics. Experience in analyzing RNAseq, GWAS, Hi-C and other large biological datasets. Familiarity with databases such as UCSC Genome Browser, 1000Genomes, TCGA, and ICGC. Experience in using standard bioinformatics packages such as Samtools, Cufflinks, Tophat. Knowledge of statistics. Knowledge of evolutionary biology, and viral/cancer immunity.
OTHER: This is a full-time salaried (exempt) position. Texas Biomed business hours are Mondays through Fridays – 8:00 a.m. to 5:00 p.m. Texas Biomedical Research Institute is committed to a drug-free workplace. Pre-employment drug screen is required.
Apply online at http://www.txbiomed.org/about/employment. Application packets are accepted electronically or in hard copy. A completed application packet is a requirement for all positions. Incomplete applications will not be accepted. Equal Employment Opportunity/M/F/Disability/Protected Veteran Status
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