EHR-Stats

Open positions

Post-doctoral Fellow

We are currently seeking candidates for a post-doctoral fellowship focusing on cutting edge population health research using Electronic Health Record (EHR) data. Under the guidance of Dr. Blanca Himes and Dr. Rebecca Hubbard, the successful applicant will be part of an interdisciplinary team that develops and applies computational methods to extract information from EHRs, and enhances EHR data with social and environmental information sourced from external resources, with a focus on asthma. The post-doctoral fellow will gain real-world experience working with EHR data, as well as have access to opportunities for networking and support for innovative work. If interested, the selected postdoc will also have opportunities to gain experience in supervising students, grant writing, and/or teaching. The position is available immediately and can be renewed annually.

Responsibilities:

• Analyze EHR data, including by incorporating environmental data from secondary sources, and perform geospatial and association analyses of asthma-related traits

• Develop and implement algorithms, statistical methods, and software to analyze EHR data that account for phenotyping error and differential availability of data elements across patients

• Develop and implement algorithms, statistical methods and software related to the identification of sub-phenotypes from clinical data 

• Communicate research progress with PIs on a regular basis and contribute to the success of the research team

• Develop and maintain productive collaborations  

• Publish and present novel research findings in academic journals and conferences

Qualifications

Candidates must have a PhD degree in biostatistics, biomedical informatics, or a related field. Preference will be given to individuals with outstanding programming skills in R or Python, a strong knowledge of Unix shell scripting, and experience in high performance computing environments. The candidate interested in this position must be highly motivated, willing to learn and demonstrate initiative in assigned tasks. Excellent written and verbal communication skills are essential.

To apply please send a cover letter, CV, and contact information for 3 references to Blanca Himes (bhimes@pennmedicine.upenn.edu)


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