Machine learning with applications to diagnostics,
at ORAU Workforce Solutions

Date Posted: 1/14/2019

Opportunity Description

Title of Research Opportunity: Machine learning with applications to diagnostics, prognostics and risk assessment Most problems in science and engineering require predictions. Predictions are invariably data driven, i.e., based on past observations or measurements. For example, we can look at past vibration patterns of a component, measure property changes, and so on, to make predictions about the state of a system and its performance. Most prediction problems can be viewed as machine learning problems where the predictors are learned from the available data. The goal of this project is to develop and test advanced machine learning algorithms suitable for diagnostics, prognostics and risk assessment of complex air systems. Emphasis is on a recent sub-field of deep-learning for big-data in the settings of supervised, unsupervised, and reinforcement learnings. We will formulate machine learning problems, identify optimal methods and assumptions needed, and specify guarantees that we might be able to provide for different methods. Click here for more information

Opportunity Snapshot

About Us

Oak Ridge Associated Universities (ORAU) administers Science, Technology, Engineering and Mathematics (STEM) research participation programs for civilians such as:

The U.S. Army Research Laboratory (ARL) Research Associateship Program (RAP) allow Postdoctoral Fellows, Journeyman Fellows (undergraduate and graduates students and recent graduates), Senior Researchers, and Summer Faculty engage in research initiatives of their own choice, that are compatible with the interests of the government and will potentially contribute to the general effort of the ARL. Scientists and engineers at ARL help shape and execute the Army's program for meeting the challenge of developing technologies that will support Army forces in meeting future operational needs.

Research opportunities include, but are not limited to the following disciplines: Aerospace Engineering, Anthropology, Archeology, Biology, Biochemistry, Biological Engineering, Biomechanical Engineering, Biomedical Engineering, Chemical Engineering, Chemistry, Computer Science, Computer Engineering, Electrical Engineering, Environmental Health Risk Assessment, Environmental Science, Entomology, Epidemiology, Ergonomics, Geology, Health Education Mechanical Engineering, Materials Science, Mathematics, Nanotechnology, Photonics, Physics, Public Health Economics, Public Health Policy, and more.

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