Post-Doctoral Associate - Clinical Pharmacogenomics
CHEManager International is seeking a Post-Doctoral Associate in Clinical Pharmacogenomics at the University of Minnesota Medical School. This role involves leading research activities to analyze genomic and clinical datasets, contributing to personalized medicine by identifying clinically actionable pharmacogenomic variants.
Responsibilities
- Lead the analysis of complex genomic and clinical datasets to identify and characterize clinically actionable pharmacogenomic (PGx) variants
- Manage a comprehensive data repository, ensuring data integrity and compliance with Institutional Review Board (IRB) protocols
- Design and execute data analysis pipelines using statistical methods and advanced computational tools
- Translate complex findings into clear data visualizations, experiment reports, and presentations for the Principal Investigator and collaborators
- Contribute significantly to the preparation of scientific manuscripts for publication and provide critical data and methods for grant proposals
- Maintain meticulous experimental records and assist in the development of Standard Operating Procedures (SOPs)
- Oversee day-to-day research operations to ensure projects progress efficiently and meet established timelines
- Serve as the primary liaison for collaborations with core facilities and clinical partners
- Coordinate and participate in weekly research team meetings to discuss progress, challenges, and next steps
- Co-author and contribute to manuscripts, reports, and scientific presentations
Skills
- PhD or PharmD in a relevant scientific field
- Demonstrated experience working in a research setting
- Strong foundation and experience in informatics, bioinformatics, and the analysis of large datasets
- Excellent organizational skills, high attention to detail, and the ability to work independently
- Superior written and verbal communication skills, with experience in scientific writing (manuscripts, grants, protocols)
- Proven experience in biomarker discovery, clinical research, or a related translational science environment
- Proficiency in coding and advanced data analysis using languages such as R or Python
- Experience working with databases using SQL, cleaning and transforming data
- Deep understanding of genomic data analysis, including next-generation sequencing (NGS) data
- A strong desire and willingness to learn new software and advanced analytical techniques as required by research activities
- Substantial experience with manuscript and grant writing
Benefits
- Competitive wages, paid holidays, and generous time off
- Continuous learning opportunities through professional training
- Medical, dental, and pharmacy plans
- Healthcare and dependent care flexible spending accounts
- University HSA contributions
- Disability and life insurance
- Employee wellbeing program
- Financial counseling services
- Employee Assistance Program with eight sessions of counseling at no cost
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