Data Scientist - Data Center Analyst
Job location: Charlottesville, VA
Employment Type: Full-time
Posted data: 2020-09-22
The Center for Advanced Medical Analytics (CAMA) in the Cardiology Division of the University of Virginia School of Medicine is seeking is seeking a talented and passionate Data Scientist to perform research on projects related to predictive monitoring using continuous physiological signals and clinical data. CAMA has collected a large repository of physiologic data and annotated clinical events that has not only produced a high volume of academic publications but has resulted in the development of applications and displays being actively used and tested out clinically with UVA Health System partners. These resources are uniquely ideal for implementing deep learning and other modern machine learning techniques. 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 have expertise in at least one of Matlab, Python, or R, and preferably should be proficient in programming using at 2 or more of Matlab, Python, R and other programs and 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 at time of employment. 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 work with undergraduate and graduate students on multiple projects along with the PI and faculty members in the Center for Advanced Medical Analytics is required.
This position is held within the Department of Medicine, Division of Cardiovascular Medicine. Position is one year with the possibility of renewal, based on funding and satisfactory performance.
Performs scientific programming for mathematical analysis of streaming physiological monitoring data. Works closely with physicians and other medical experts to understand clinical significance of projects. Collaborates with other members of the large clinical and engineering team. Manages large, complex data sets and utilizes high performance computing resources as needed.
1) Ability to be self-motivated.
2) Ability to work well with teams.
3) Ability to serve as a technical liaison.
4) Ability to manage large, complex data sets across multiple sites.
5) Ability to perform scientific programming for mathematical analysis of streaming physiological monitoring data.
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, and Matlab
Required: Expertise in one of Python, R, or Matlab.
To apply please visit UVA job board https://uva.wd1.myworkdayjobs.com/UVAJobs, and search for "R0018829" Complete the application and see below for documents to attach.
Required Application Materials:
- Cover Letter
- Contact information for 3 references
Please note multiple documents can be submitted in the CV/Resume Box. Applications that do not contain all of the required documents will not receive full consideration.
The selected candidate will be required to complete a background check at time of offer per University Policy.
The University of Virginia, including the UVA Health System which represents the UVA Medical Center, Schools of Medicine and Nursing, UVA Physician’s Group and the Claude Moore Health Sciences Library, 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 or expression, marital status, national or ethnic origin, political affiliation, race, religion, sex (including pregnancy), sexual orientation, veteran status, and family medical or genetic information.