Post-Doctoral Research Associate - Computational Biologist

Post-Doctoral Research Associate - Computational Biologist

Job Title:

Post-Doctoral Research Associate - Computational Biologist

Job Description

Summary:

The Oakland University Institute for Data Science, in conjunction with scientists at the University of Michigan and Harvard have recently formed a collaborative American Heart Association funded Strategically Focused Research Network ((Use the "Apply for this Job" box below).). This network has been established to focus on the interrelated domains of heart and brain health and aims to bring participating researchers together to unravel the biological mechanisms that the heart and brain have in common, as well as how these organs signal to each other and impact clinical outcomes.

Despite the recognized interconnectedness of these health areas, especially in relation to metabolic, neurodegenerative, neurological, and neurocognitive disorders, few, if any, platforms offer integrated research solutions in this space. The role of the Institute for Data Science is to provide a computational platform that will be the heart of data analytics for this research network.

We are searching for a highly motivated and computationally skilled individual to join the team interested in harnessing, merging, and sharing data, algorithms, and computational resources to discover innovative insights, launch clinical and translational research studies, and evaluate treatments arising from our collaborative research efforts that relate heart and brain health and disease(s). The selected candidate will focus on methods for analyzing diverse data types and integrating ’omics expression data, imaging data, and wearable sensors data.

The data types included will range from patient-specific to aggregated data, spanning the continuum of genetics, multi-omics, metabolomics, physiologic/wearable data, tissue, organ, imaging data, and patient-specific longitudinal electronic health record (EHR) data, including relevant Social Determinates of Health (SDOH) and geospatially encoded demographic and health outcomes data.

Minimum Qualifications:

Recent PhD in computational Biology, Statistics, Computer Science or related field. Deep understanding of next generation sequencing data and bioinformatics algorithms. Provide best practices data analysis, including QC and visualization, employing common NGS pipelines such as RNA‑seq, ChIP‑seq, ATAC‑seq, Methyl‑seq, DNA‑seq, and Microbiome Sequencing. Multi‑omics analysis is often needed. Proven experience working in a Linux cluster environment. Experience in cloud environments is also a plus.

Familiarity with analysis of Biobank data, human microbiome sequence data (16S rRNA, metagenomics) and/or multi‑omics data (e.g. transcriptomics or metabolomic). Strong background in one or more of the following: pedigree analysis, machine learning, statistical methods, variant annotation and interpretation, Genome Wide Association Studies (GWAS), imaging analysis, and wearable sensor data analysis. Knowledge of general principles for regulatory compliance, including understanding of the NIH Security Best Practices for Controlled Access Data Subject to the NIH Genomic Data Sharing (GDS) Policy (aka dbGaP compliance).

Experience with project management.

• Curriculum Vitae (CV)
• Cover Letter
• Transcripts (unofficial)

Oakland University is an affirmative action/Equal Opportunity Employer and encourages applications from women and minorities.

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