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.
Requirements:
The ideal applicant would have a doctorate level degree (PhD, MD, or MD/PhD) in clinical informatics, data science, implementation 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.
He or she should be very skilled in programming and computational data science, with some experience in IT systems. The candidate should have demonstrated experience with programming languages (e.g., R, python, perl) and relational database structures (e.g., SQL).
Expectations:
The post-doctoral scientist will work with clinicians and scientists within the Mount Sinai Health System, as well as other institutions across the United States and Europe as part of the Smart4Health grant and on internal projects. The technical approaches used will emphasize data mining, statistics, ontological frameworks, and data science. This position is highly collaborative and applicants must be comfortable in a dynamic research environment comprised of students and staff from diverse backgrounds. He or she will be working under the mentorship of Dr. Benjamin Glicksberg. The candidate will be highly encouraged to publish their work in journals and present in national and international conferences.
Primary responsibilities:
- Lead coordination and research efforts for Citizen Use Case (CUC) 1 as a key site within the Smart4Health grant.
- Help develop novel schemas for capturing and integrating multi-modal health data (e.g., genetics, imaging) into OMOP EHR Common Data Model frameworks.
- Help quality control (QC) and quality improve (QI) the data streams from ISMMS and other sites, particularly in the OHDSI OMOP CDM framework.
- Develop clinical and epidemiological research questions that leverage a vast network of data from different countries.
- Work on other ISMMS-specific personalized medicine projects that involve such data.
- Present at national and international meetings.
Applicants are requested to send:
- CV that includes a list of publications
- Details of 3 references.
- Link to repository with examples of code (e.g., GitHub).
All inquiries regarding the position are welcome and can be sent to benjamin.glicksberg@mssm.edu.
The Icahn School of Medicine at Mount Sinai is an Equal Opportunity/Affirmative Action Employer —Race/Gender/Disability/Veteran.
Tagged as: Computer Science, Life Sciences, Mathematics
