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Computational Scientist: Cancer Immunogenomics Specialist
2 months ago
Job Summary:
BEPC Inc. - Business Excellence Professional Consulting is seeking a highly skilled and motivated Computational Scientist to join our team in the field of Cancer Immunogenomics. The successful candidate will have a strong analytical background in computational biology and immuno-oncology, with a focus on T cell biology.
Key Responsibilities:
- Collaborate with scientists in Oncology to analyze large-scale single-cell and bulk RNA, TCR, ADT, and ATAC-seq datasets to address scientific hypotheses and deliver novel insights.
- Develop analytical approaches to integrate and interpret these data, delivering insights into disease biology and mechanisms of action to propel our pipeline and clinical research goals.
- Coordinate the processing and standardization of newly incoming datasets to make them analysis ready.
- Document code, analysis processes, and findings, including standardization of analytical workflows.
- Present findings to the Cancer Immunogenomics group and Oncology collaborators.
Requirements:
- Extensive experience in large-scale single-cell data analysis (RNA, TCR, ADT, ATAC), including gold-standard methods and novel, advanced analytical techniques such as: Multimodal data integration methods
- Cell phenotyping approaches, including topic modeling
- Clonotype analysis
- TCR-sequence analysis
- Expertise in (immuno)-oncology, innate immunity, and/or T cell biology.
- PhD (or Master's with significant experience) in Computational Biology, Bioinformatics, or a related field.
- Proficiency in R, Python, and shell scripting.
- Experience working with Git and high-performance computing.
- High self-motivation and commitment to delivering high-quality results.
- Ability to produce high-quality analysis results with minimal supervision, including meeting key deadlines and making sensible independent decisions.
- Excellent communication skills and experience working as part of a team.
- Curiosity and desire to learn more about computational biology and immuno-oncology biology.
