The Seney Lab (https://seneylab.pitt.edu in the Translational Neuroscience Program and Department of Psychiatry at the University of Pittsburgh is seeking a highly motivated Research Principal to join an interdisciplinary research team studying the molecular and systems-level biology of psychiatric and substance use disorders. Our lab integrates large-scale omics data with behavioral phenotypes to understand mechanisms underlying brain disorders and to identify novel therapeutic targets. This position offers the opportunity to work on cutting-edge, data-intensive projects in a collaborative environment alongside neuroscientists and computational researchers.
Join a collaborative and supportive research lab at a top-tier research institution where we offer opportunities for professional development, authorship, and conference presentations.
This position is grant funded.
Responsibilities:
Analyze and interpret high-dimensional biological data, including transcriptomic (e.g., bulk and single-cell RNA-seq, epigenetic, and proteomic datasets
Develop, implement, and maintain statistical and computational analysis pipelines
Apply rigorous statistical methods to experimental design, hypothesis testing, and data interpretation
Collaborate closely with experimental scientists to translate biological questions into analytic strategies
Contribute to manuscript preparation and data visualization
Document workflows and ensure reproducibility of analyses
Masters degree required preferably in Psychology, Neuroscience, Counseling, Sociology, Biostatistics, Bioinformatics, Computational Biology, Statistics, Data Science, or related research field
Minimum of two years of work experience in a research project and/or related clinical setting is required
Familiarity with computers and common software packages required
Working knowledge of research methodology required
Prior supervisory experience preferred
Strong programming skills in R preferred
Experience working with large, complex biological or biomedical datasets preferred
Solid foundation in statistical modeling and data analysis preferred
Ability to work independently while contributing effectively to a team-based research environment
Experience with RNA-seq and/or single-cell sequencing data preferred
Familiarity with genomic analysis tools and pipelines (e.g., Bioconductor, DESeq2, Seurat preferred
Knowledge of experimental design in biological research preferred
Experience with version control (e.g., Git and reproducible research practices preferred
Prior publication record or demonstrated contribution to peer-reviewed research preferred
Licensure, Certifications, and Clearances:
UPMC is an Equal Opportunity Employer/Disability/Veteran