13 дней назад
Associate Scientist – Digital Discovery: Antibody Bioinformatics
92 476 - 125 115CAD
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Описание вакансии
Текст:
TL;DR
Associate Scientist – Digital Discovery: Antibody Bioinformatics (biotech, BCR-Seq, R/Python): Running antibody discovery workflows and analyzing BCR repertoire, NGS, single-cell, protein, and related biological datasets with an accent on data quality, curation, and reproducible analysis. Focus on developing analytical tools, integrating experimental metadata, and connecting wet-lab workflows with downstream computational discovery decisions.
Location: Burnaby, Canada
Salary: CAD 92,476.60–125,115.40
Company
is a biotechnology company developing medicines for serious illnesses across oncology, inflammation, general medicine, rare disease, and obesity-related conditions.
What you will do
- Run antibody discovery computational workflows, assess sequencing and data quality, and analyze antibody repertoires and candidate sequences.
- Analyze BCR repertoire, NGS, single-cell, protein, and related antibody discovery datasets.
- Develop R and/or Python scripts, analytical tools, reports, and visualizations for downstream BCR-Seq analysis.
- Organize, curate, and integrate BCR-Seq, antibody screening, experimental data, and metadata.
- Work with wet-lab scientists to improve data capture, traceability, quality, and experimental-to-computational handoffs.
- Communicate analytical findings through visualizations, scientific summaries, and collaborative problem-solving.
Requirements
- Master’s degree with at least 1 year of relevant experience, or Bachelor’s degree with at least 3 years of relevant experience, in biological sciences, biochemistry, molecular biology, immunology, bioinformatics, computational biology, or a related field.
- Hands-on experimental experience in molecular biology, immunology, biologics or antibody discovery, genomics, NGS, protein characterization, or a related discipline.
- Training or experience in bioinformatics, computational biology, scientific informatics, or biological data analysis.
- Working knowledge of R and/or Python for biological data analysis, visualization, and scripting.
- Experience with complex experimental datasets, metadata, data curation, integration, quality control, and documentation.
- Strong communication, organization, and collaboration skills across experimental and computational disciplines.
Nice to have
- Experience with SQL, NGS, immune repertoire, single-cell, flow cytometry, or other high-dimensional biological datasets.
- Familiarity with Cell Ranger, Seurat, Scanpy, FlowJo, Bioconductor, or comparable platforms.
- Familiarity with Linux and command-line environments, reproducible analysis, cloud or HPC environments, Benchling, ELNs, or LIMS.
Culture & Benefits
- Collaborative, innovative, and science-based working environment.
- Competitive benefits and comprehensive total rewards aligned with local industry standards.
- Support for professional growth and personal well-being.
- Inclusive workplace focused on advancing science and improving patients’ quality of life.
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