The University of Pennsylvania is seeking a Data Scientist to lead and support advanced computational biology and biomedical informatics research, focusing on integrating and analyzing large-scale clinical, genomics, proteomics, imaging, and informatics data to enable high-impact discoveries and build shared infrastructure.
Requirements
- Experience with machine learning or deep learning applications in biomedical research.
- Proficiency in Python, R, or comparable programming languages; experience with HPC or cloud-based environments.
Responsibilities
- Lead the design, development, and execution of computational genomics, multi-omics integration, and biomedical informatics projects in collaboration with the principal investigators.
- Collaborate with PIs and PMBB Clinical Informatics and Genomics Core on projects that leverage imaging-derived phenotypes, including working with AI and deep learning methods to extract features from medical images and integrating these into downstream analyses.
- Develop and maintain computational pipelines for phenotype generation, data harmonization, and integration across clinical, imaging, and genomic datasets.
- Oversee data analysis workflows to ensure methodological rigor, reproducibility, and scalability.
- Apply statistical genetics and bioinformatics methods to conduct biobank-scale analyses.
- Provide computational expertise and support to collaborators, including phenotype generation and downstream analysis.
- Coordinate with other cores and research groups to build shared infrastructure and tools that expand the impact of PMBB and related resources.
Other
- Master of Science and 1 to 2 years of experience, or an equivalent combination of education and experience.
- PhD in Computational Biology, Bioinformatics, Statistical Genetics, Computer Science, or a related field strongly preferred.
- Strong record of research in statistical genetics or large-scale omics analysis.
- Strong publication record in data science, computational biology or related fields.
- Excellent communication skills and experience working in cross-disciplinary collaborations.
