Job description
Bioinformatics Scientist
Arcus is seeking a Bioinformatics Scientist that will work in a highly embedded, collaborative model with colleagues across the organization. Position title would be commensurate with years of relevant experience.
The scientist will be expected to work effectively on highly technical interdisciplinary teams and be driven to pursue creative solutions to challenging problems. The successful applicant will be expected to take the lead in providing Bioinformatics expertise to cross functional project teams working on drug discovery and biomarker development. They will use their bioinformatics expertise to develop bioinformatics strategies, help plan collaborative experiments, and analyze high-dimensional molecular datasets to help understand the molecular mechanism and biological effects of our therapeutics.
The individual may also support internal infrastructure and framework development to enable efficient execution of the above roles and facilitate better information exchange across departments.
Responsibilities:
Preferred Experience:
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Arcus is seeking a Bioinformatics Scientist that will work in a highly embedded, collaborative model with colleagues across the organization. Position title would be commensurate with years of relevant experience.
The scientist will be expected to work effectively on highly technical interdisciplinary teams and be driven to pursue creative solutions to challenging problems. The successful applicant will be expected to take the lead in providing Bioinformatics expertise to cross functional project teams working on drug discovery and biomarker development. They will use their bioinformatics expertise to develop bioinformatics strategies, help plan collaborative experiments, and analyze high-dimensional molecular datasets to help understand the molecular mechanism and biological effects of our therapeutics.
The individual may also support internal infrastructure and framework development to enable efficient execution of the above roles and facilitate better information exchange across departments.
Responsibilities:
- Perform collaborative research with cross-functional groups to study immuno-oncology – jointly identify key issues, set goals, and lead and execute bioinformatics functions for programs.
- Identify relevant datasets and strategies to augment growing internal database of multimodal high-dimensional datasets.
- Analyze multiomics datasets using cutting edge algorithms and rigorous statistical methods to support drug development pipelines.
- Serve as a scientific resource to discovery R&D and translational programs.
- Communicate bioinformatics analyses and strategies to company-wide audiences to guide company goals and inform drug development.
- Develop reproducible frameworks, computational methods, and infrastructure to analyze high-dimensional biological data into actionable clinical findings and research insights.
- PhD in Bioinformatics, Biostatistics, Computational Biology, Computer Science, or similar field, ideally in the field of cancer, immunology, and/or immuno-oncology.
- 2+ years of Life Science experience with the demonstrated ability to lead a project with an independent research responsibility as evidenced by a track record of publications, conference presentations, or invited talks.
- Strong understanding of oncology and/or immunology concepts and applications.
- Proven expertise in working with human or mouse transcriptomics datasets and other high-dimensional datasets to understand biological mechanisms or discover novel biomarkers.
- Coding expertise in languages such as R and/or Python for bioinformatics analyses.
- Experience in version control and collaborating with other bioinformatics scientists/engineers.
- Demonstrated ability to present complex results, both verbally and in writing, to bioinformatics and non-bioinformatics audiences of all levels is critical.
- Comfortable working in a matrix environment and handling several concurrent fast paced projects.
Preferred Experience:
- Familiarity with integrating molecular and clinical data and performing survival analyses.
- Experience with various high-dimensional data platforms such as scRNA-seq or proteomics.
- Experience in developing machine and/or deep learning models to support various bioinformatics campaigns.
- Familiarity with a pipeline manager or workflow language such as Snakemake or Nextflow.
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