University of Pittsburgh
Data Analyst (Finance)
The successful applicant must be proficient with Python, Unix/Linux and have used software repositories such as Git and demonstrate familiarities with machine learning and statistics in particular, in order to work with a high level of autonomy. As a member of a team conducting novel biomedical research, a successful applicant will need to pre-process imaging data, run the pipeline developed by other members of the lab, and summarize the results. Detailed work with end-users and other researchers will be required, often with the implicit requirement of learning the details of a new and unfamiliar field.
Success in this position will require working closely with graduate students and postdocs. DBMI uses state-of-the-art software tools and systems to support cutting-edge biomedical research. DBMI is currently working on projects involving big data including large-scale electronic health record data, genomic data, information integration for personalized medicine, creating distributed research data networks, and related topics united under the common theme of translational informatics using information systems to move basic scientific insights into meaningful medical care. In addition, DBMI is the home to a large graduate training program in biomedical informatics.
Bachelor's degree in Computer Science, Electrical Engineering, Biomedical Engineering, Mathematics, Statistics, Economics or comparable field required. Experience with Python programming language; experience in additional languages (R, MATLAB) is a plus. Familiarity with one of the deep learning frameworks is a plus (PyTorch or Tensorflow). Experience with medical image data analysis is highly desirable. Familiarity with broad range of statistical methods such as parametric and non-parametric tests of significance, linear and logistic regression; some longitudinal analysis experience is desirable.