The Stanford Bioinformatics Center for the Molecular Transducers of Physical Activity Consortium is seeking a postdoctoral scholar to engage in high impact bioinformatic and multi-omic research in the fields of exercise biology and cardiovascular.
Specifically, work will focus on analysis and integration of high dimensional multi-omic data with metrics of exercise performance in the Molecular Transducers of Physical Activity Consortium (MoTrPAC) and related studies, including data from both human and animal studies. Applicants with bioinformatics, multi-omics, and computational biology experience are desirable, and highly qualified applicants will have experience with cloud computing and web interface development.
Our group engages in diverse work across the spectrum of investigation, spanning computational dry lab expertise in proteomics, metabolomics, transcriptomics, genetics, bioinformatics, machine learning, and artificial intelligence, offering varied avenues for mentoring and professional development. Multiple opportunities exist for national collaboration in a variety of consortia including not only MoTrPAC, but also the Common Fund Data Ecosystem and the Undiagnosed Disease Network.
Key research avenues include:
Integration of human and animal data to understand systemic responses to exercise. Development of novel data integration techniques across multi-modal data, including omics and assessments of physical fitness. Development of cloud-based infrastructures for data browsing, interactivity, and discovery, in MoTrPAC and others Additional avenues of work to be determined with the applicant
- Ph.D. in a relevant field (e.g., molecular biology, bioinformatics, computer science).
- Strong background in data analysis and computational biology.
- Proficiency in programming languages such as R and Python.
- Excellent communication skills, both written and verbal.
- Ability to work independently and collaboratively in a dynamic research environment.
Preferred Qualifications:
- Experience with large-scale multi-omic datasets and/or bioinformatics tools.
- Demonstrated track record of scientific productivity (e.g., publications, presentations).
