Research Associate

Research Associate

The Dr. Gupta Laboratory in the Department of Ophthalmology and Visual Sciences at the University of British Columbia is seeking a full-time (100% FTE) Research Associate (Computational Biology and Translational Bioinformatics) to support an innovative translational research program investigating the molecular mechanisms underlying ocular and neurodegenerative diseases.

The successful candidate will bring expertise in computational biology and bioinformatics to a multidisciplinary research team, applying advanced computational approaches to integrate multi-omics and imaging datasets, identify candidate disease mechanisms, therapeutic targets, and biomarkers, and support studies spanning ocular biology, neuroscience, and translational medicine. Working closely with laboratory scientists, the successful candidate will integrate computational analyses with experimental research and contribute to scientific publications, the preparation of competitive grant applications, and the advancement of the laboratory's research program.

Responsibilities:

• Design, implement, and manage computational biology and translational bioinformatics analyses supporting multidisciplinary research projects.
• Analyze, integrate, and interpret genomic, transcriptomic, proteomic, lipidomic, spatial multi-omics, imaging, and other high-dimensional biological datasets.
• Identify candidate molecular pathways, disease mechanisms, therapeutic targets, and biomarkers through integrative computational analyses.
• Develop reproducible computational workflows and data visualization tools to support biological interpretation and hypothesis generation.
• Integrate computational analyses with molecular, cellular, and immunological studies in collaboration with laboratory scientists.
• Develop and/or adapt machine learning and artificial intelligence approaches for the analysis of spatial and multispectral imaging datasets, including transcriptomic, proteomic, and lipidomic data derived from tissue specimens and cell culture models.
• Prepare figures, reports, manuscripts, and presentations for scientific publications, grant applications, and research meetings.
• Contribute to the preparation of competitive grant applications and research documentation.
• Provide technical expertise, mentorship, and training in computational biology and bioinformatics to trainees and laboratory personnel.
• Work collaboratively with multidisciplinary research teams and external collaborators.
• Perform other related duties as required.

  Supervision Received:

  Works independently under the direction of Dr. Neeru Gupta.

  Supervision Given:

  May provide mentorship and technical guidance to undergraduate and graduate students, research assistants, and other laboratory trainees

  Qualifications:

  • PhD in Computational Biology, Bioinformatics, Genomics, Systems Biology, Computer Science, Biomedical Engineering, Molecular Biology, or a related discipline, with a minimum of three years of relevant postdoctoral or equivalent research experience, or an equivalent combination of education, training, and experience.
  • Demonstrated experience analyzing genomic, transcriptomic, proteomic, lipidomic, or other high-dimensional biological datasets, including next-generation sequencing data.
  • Proficiency in R and/or Python for computational biology and bioinformatics analyses.
  • Strong background in statistical analysis, data integration, and scientific data visualization.
  • Experience developing reproducible computational workflows and managing large-scale biological datasets.
  • Experience working collaboratively in a multidisciplinary biomedical research environment.
  • Excellent written and verbal communication skills, with demonstrated contributions to peer-reviewed scientific publications.
  • Knowledge of molecular biology, cell biology, immunology, neuroscience, or ophthalmic research is considered an asset. Experience with single-cell genomics, spatial transcriptomics, spatial proteomics, multi-omics integration, machine learning, artificial intelligence, or drug discovery and development in the pharmaceutical or biotechnology industry is considered an asset.