Chikina Lab Post Doctoral Associate

Join the Chikina Lab in the Department of Computational and Systems Biology at the University of Pittsburgh School of Medicine as a full-time Postdoctoral Research Fellow in computational biology.

About the role

The successful candidate will conduct computational and quantitative biomedical research aimed at improving the understanding of biological processes in complex tissues. The research will involve the development, evaluation, and application of methods for studying cellular composition and cell-type-related molecular patterns in tissue-level gene expression data. The fellow will also apply these approaches to spatially resolved transcriptomic data and may integrate molecular measurements with pathology images when scientifically appropriate.

This position provides an opportunity to receive advanced training in computational method development, transcriptomic data analysis, spatial biology, and biological interpretation. The fellow will work under the supervision of Dr. Maria Chikina and will have opportunities to develop research projects, prepare scholarly publications, present research findings, and expand expertise in quantitative biomedical research.

Responsibilities

• Develop, evaluate, and apply computational methods for biological data analysis
• Analyze bulk, single-cell, spatial transcriptomic, and tissue-imaging data
• Interpret findings in the context of biological processes and tissue organization
• Develop reproducible analysis workflows and maintain accurate research documentation
• Prepare manuscripts, abstracts, presentations, and other scholarly materials
• Present research progress at laboratory meetings, seminars, and scientific conferences

Requirements

• A Ph.D. or equivalent doctoral degree in computational biology, bioinformatics, quantitative biology, genomics, biomedical engineering, or a closely related field by the position start date
• Research experience in the computational or quantitative analysis of biological data
• Proficiency in R, Python, or another scientific programming language
• Experience analyzing transcriptomic, genomic, molecular, or other high-dimensional biological data
• Strong written and oral scientific communication skills
• Evidence of research productivity, such as publications, manuscripts, or conference presentations

Required attachments: Cover Letter, Curriculum Vitae