• University of Virginia Health System
  • $97,050.00 -151,690.00/year*
  • Charlottesville, VA
  • Information Technology
  • Full-Time
  • 589 McCormick Rd

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The Data Engineering Laboratory in the University of Virginia School of Medicine, Department of Public Health Sciences (PHS), is seeking is seeking a talented and passionate Data Scientist to perform research on projects related to data engineering, predictive analytics, and monitoring using continuous physiological signals, longitudinal clinical data, and other information related to patient health.

The successful candidate will work with medical, research and data science colleagues in the School of Medicine, the Data Science Institute, and other clinical research departments of the University. One particular focus of this work will be a collaboration with the Center for Advanced Medical Analytics (CAMA) on deep learning and other modern machine learning techniques applied to continuous physiologic data.

Additional projects may involve collaborations with the Brain Institute, the Department of Psychology, and other departments doing human subjects health research; and with UVA Health System Analytics and UVA VP of Information Technology staff, to help develop instrumented computational workflow systems as part of a federated data commons architecture.

Candidates are sought with expertise in supervised and unsupervised learning methods such as convolutional neural networks, recurrent neural networks, autoencoders, random forests and logistic regression. Candidates must be proficient in programming using Matlab, Python, R and other languages; and the associated machine learning libraries and packages.

Candidates should have experience in the application of machine learning techniques to physiological data. Analytics support is needed for research on physiological monitoring including: advanced mathematical and statistical analysis in order to develop and deploy algorithms for early detection of illness, large-scale time series and other data acquisition. Qualified applicants must have a Master's degree or higher in Data Science, Computer Science, Mathematics, systems administration, Systems Engineering, Electrical Engineering, or other engineering disciplines. A formal background in mathematics and statistics is preferred.

In addition, candidates should have excellent oral and written communication skills with the ability to present at professional meetings. The ability to supervise undergraduate students on multiple projects along with the PI and faculty members in PHS, CAMA, and other departments is highly desirable. This position is held within the Department of Public Health Sciences, in the School of Medicine. Positions are one year with the possibility of renewal, based on funding and satisfactory performance.

Preferred experience in any of the following fields: bioinformatics, computational statistics, data analytics, signal processing. Experience with at least two of the following programming languages: C++, Python, R, Java, Matla.

The University of Virginia, including the UVA Health System and the University Physicians Group are fundamentally committed to the diversity of our faculty and staff. We believe diversity is excellence expressing itself through every person's perspectives and lived experiences. We are equal opportunity and affirmative action employers. All qualified applicants will receive consideration for employment without regard to age, color, disability, gender identity, marital status, national or ethnic origin, political affiliation, race, religion, sex (including pregnancy), sexual orientation, veteran status, and family medical or genetic information.


Associated topics: data administrator, data analytic, data integration, data management, data quality, data scientist, data warehouse, data warehousing, database administrator, mongo database administrator
Associated topics: data administrator, data architect, data manager, data warehouse, data warehousing, etl, erp, hbase, mongo database administrator, sybase

* The salary listed in the header is an estimate based on salary data for similar jobs in the same area. Salary or compensation data found in the job description is accurate.

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