Research Associate

Note: Applications will be accepted until 11:59 PM on the Posting End Date.

Job End Date

August 23, 2028

The expected pay (or pay range) for this position is $6,344/month.

Job Description

• 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

Successful applicants will have

• 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.