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- The Hasso Plattner Institute of Digital Health at the Icahn School of Medicine at Mount Sinai (ISMMS) is looking for a post-doc to lead research pertaining to analysis of massive amounts of patient data for real world data studies to forward personalized medicine. The candidate would have access to unparalleled health data resources including Electronic Health Records of over 8 million patients, some of whom have linked genomic and imaging data (https://msdw.mountsinai.org/).
The candidate will lead efforts from the Smart4Health (www.smart4health.eu) international collaboration. Simply, Smart4Health will develop, test and validate a platform prototype for a new citizen-centered health record with integrated abilities for aggregation of data, for sharing and for data provision/donorship to the scientific community. ISMMS’ role in this grant is to use our powerful data to serve as a foundation for a research platform, which hospitals from European countries will join. The candidate will have the unique opportunity to help form this foundation and perform research across millions of patients across many countries. The candidate will work with research leads across these institutions, including Data4Life (https://www.data4life.care/en/). The candidate will also be able to work on ISMMS-specific projects that utilize machine learning on patient health data for precision medicine discoveries
1. Lead coordination and research efforts for Citizen Use Case (CUC) 1 as a key site within the Smart4Health grant.
2. Help in setting up the research platform that will be used to ingest data from hospitals across Europe.
3. Help quality control (QC) and quality improve (QI) the data streams from ISMMS and other sites, particularly in the OHDSI OMOP CDM framework.
4. Develop clinical and epidemiological research questions that leverage a vast network of data from different countries.
5. Work on other ISMMS-specific personalized medicine projects that involve such data.
6. Present at national and international meetings.
- The ideal applicant would have a doctorate level degree (PhD, MD, or MD/PhD) in clinical informatics, data science, or bioinformatics. However, a non-biological background with strong training in another area of data science, particularly statistics, epidemiology, computer science, physics, or mathematics may be appropriate. All candidates should have strong publication track record and experience with Electronic Health Records research. Experience with Common Data Models, such as OMOP CDM from OHDSI, is an advantage.