Bioinformatics Research Analyst Department of Oncology

Wayne State University is searching for an experienced Bioinformatics Research Analyst - Department of Oncology at its Detroit campus location.

Wayne State is a premier public urban research university located in the heart of Detroit Michigan where students from all backgrounds are offered a rich high-quality education. Our deep-rooted commitment to excellence collaboration integrity diversity and inclusion creates exceptional educational opportunities which prepare students for success in a global society.

Provide computational and analytic support for a cancer genetic epidemiology research program focused on genomic determinants of cancer susceptibility and outcomes. Under the direction of the Principal Investigator develop and execute reproducible workflows for large-scale genomic EHR-linked and multi-omic data; perform statistical genetic analyses; interpret results; and contribute to collaborative scientific outputs. The position reports to the Professor Oncology.

Education: Masters degree

Masters degree from an accredited college or university in Bioinformatics Computational Biology Statistical Genetics Genetic Epidemiology Biostatistics Data Science or a related quantitative field.

Experience: Entry level (One year of job-related experience)

Prior research experience analyzing human genomic or other high-dimensional biological data including quality control analysis and interpretation of human genetic data derived from whole-genome sequencing whole-exome sequencing array genotyping and/or other genomic technologies required.

Experience performing genomic data quality control data harmonization variant annotation and statistical analysis required.

Experience working with large population or clinical research datasets including EHR-linked genomic cohorts preferred.

Graduate research and internships experience preferred; MS research project experience is acceptable.

Experience with Hail SQL or relational databases Git/version control cloud-based genomic analysis PRS Mendelian randomization gene-environment interaction analysis or multi-omics integration preferred.

Experience with Python preferred.

Knowledge Skills and Abilities:

Proficiency in R for data manipulation statistical analysis and visualization.

Working knowledge of Unix/Linux shell scripting and command-line bioinformatics tools.

Familiarity with common human-genetics data formats including VCF/BCF PLINK BED/BIM/FAM or PGEN/PVAR/PSAM BED interval files and GWAS summary-statistic files.

Ability to work with large-scale genomic datasets in cloud-computing or high-performance computing environments including efficient management and analysis of datasets that cannot be processed locally.

Familiarity with large genomic and population resources such as All of Us UK Biobank dbGaP gnomAD 1000 Genomes and TOPMed.

Knowledge of human genetic association methods including single-variant association testing gene- or region-based analysis population stratification and ancestry adjustment GWAS rare-variant analysis and interpretation of association results.

Ability to develop clear reproducible well-documented analytic code and computational workflows including appropriate quality control and validation steps.

Strong quantitative reasoning and troubleshooting skills including the ability to identify and resolve problems involving data structure computational pipelines statistical models and unexpected analytic results.

Ability to critically interpret genetic and genomic results and communicate findings clearly to the Principal Investigator scientific collaborators and multidisciplinary research teams.

Ability to manage multiple analyses simultaneously maintain organized analytic documentation meet project deadlines and adapt to evolving research questions and methods.

Ability and willingness to independently learn new statistical computational and bioinformatic methods as required by research projects.

Familiarity with integration and interpretation of multiple genomic data types including sequencing transcriptomic epigenomic and chromatin-accessibility data.

Strong written and verbal communication skills and the ability to contribute to scientific presentations manuscripts abstracts and collaborative research discussions.

H06 - School of Medicine

H0632 - Oncology

• Regular Employee
• Job type: Full Time
• Job category: Research

• Compensation type: Annual Salary

Normal office and computational research environments.

• Number of openings: 1
• Reposted position: No
• Reposted reason: None (New Requisition)
• Prior posting/requisition number:

University policy requires certain persons who are offered employment to undergo a background check including a criminal history check before starting work. If you are offered employment the university will inform you if a background check is required.

Required Experience:

IC