Research Principal

UPMCPittsburgh, PA

About The Position

The Seney Lab 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. This position is grant funded.

Requirements

  • 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

Nice To Haves

  • 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

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

Benefits

  • opportunities for professional development
  • authorship
  • conference presentations
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