Postdoctoral Research Associate in Systems Medicine
- PhD qualified in relevant subject area (or pending results).
- Strong programming skills with proficiency in Python, R, and tools relevant to multi-omics data analysis (e.g., CellRanger, GECKO, tINIT)
- Demonstrated ability to work independently, manage time effectively, and meet competing deadlines in a dynamic research environment
- Experience in analyzing large-scale multi-omics datasets, including transcriptomics, proteomics, and metabolomics, using advanced statistical and computational methods
- Familiarity with genome-scale metabolic models (GEMs) and familiarity with flux balance analysis or other metabolic flux modeling approaches
- Ability to communicate effectively within a multi-disciplinary team and produce high-quality verbal and written reports and publications
- Knowledge of liver disease, cancer and/or metabolism
- Strong problem-solving skills and the ability to develop novel computational methods for data integration and analysis
- Experience with machine learning approaches for biological data modeling and predictive analytics
- Good communication skills and willingness to work within a multi-disciplinary group.
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