Regeneron Genetics Center (RGC) is seeking to pioneer the analysis of large-scale proteomic datasets, with a special emphasis on aging and age-related diseases. The role aims to develop and apply proteomic-based predictive models at scale, integrate multi-omic datasets, improve data harmonization and portability, and identify therapeutic targets.
Requirements
- Proficiency in Python and R, with familiarity in workflow languages such as WDL.
- Demonstrated expertise in machine learning and predictive analytics applied to biological data.
- Strong understanding of multi-omic data integration and its application in therapeutic target discovery.
- Experience in developing and implementing methods for data harmonization and normalization.
- At least 3 years of post-PhD experience in analyzing large-scale omics datasets, with a focus on proteomics.
Responsibilities
- Plan, develop, and execute large-scale analyses of proteomic datasets, with an emphasis on aging and age-related diseases.
- Utilize machine learning techniques to build predictive models and generate insights from multi-omic datasets.
- Develop and implement methods for data harmonization and normalization across distinct cohorts to ensure consistency and reproducibility of results.
- Integrate proteomic, genomic, and other multi-omic data to improve therapeutic target discovery and prioritization.
- Lead the development of reproducible workflows and pipelines for multi-omic data analysis.
- Collaborate with cross-functional teams to drive large-scale omics projects and support translational research goals.
- Stay abreast of emerging trends in proteomics, machine learning, and multi-omics to continuously enhance analytical strategies.
Other
- Proven ability to independently lead and manage research projects from conception to completion.
- Excellent communication and collaboration skills, with a track record of working effectively in interdisciplinary teams.
- A PhD, MD, or MD/PhD in a relevant field (e.g., bioinformatics, computational biology, genetics, or related disciplines).
