What are the responsibilities and job description for the Learning-based Modeling Approach for Information Asset Valuation and Selection position at DEVCOM Army Research Laboratory?
About the Research
This research opportunity is to develop novel methods for information assets selection and content filtering from high dimensional data. Specifically, the opportunity will develop and validate an approach for context aware and adaptive learning models for selecting the most relevant and valuable information assets from high dimensional streaming data and quantification approaches to confidence levels on the models. Specifically, this project focuses on utilizing state-of-the-art machine learning algorithms to dynamically adapt to, or learn from human or agent actions and contextual situations and environments.
Keywords: AI, Machine Learning, Computational modeling, Optimization, Distribution theories, Statistical Inference, Modeling, and Simulation
ARL Advisor: Jade Freeman
ARL Advisor Email: jade.l.freeman2.civ@mail.mil
ARL Co-Advisor: Jesse M Milzman
ARL Co-Advisor Email: jesse.m.milzman.civ@army.mil
About Army Research Directorate (ARD)
ARL’s Army Research Directorate (ARD) focuses on exploiting concept development, discovery, technology development, and transition of the most promising disruptive science and technology to deliver to the Army fundamentally advantageous science-based capabilities through laboratory’s 11 research competencies. This intramural research directorate also manages the laboratory’s essential research programs, which are flagship research efforts focused on delivering defined outcomes.
About ARL-RAP
The Army Research Laboratory Research Associateship Program (ARL-RAP) is designed to significantly increase the involvement of creative and highly trained scientists and engineers from academia and industry in scientific and technical areas of interest and relevance to the Army. Scientists and Engineers at the CCDC Army Research Laboratory (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 by pursuing scientific research and technological developments in diverse fields such as: applied mathematics, atmospheric characterization, simulation and human modeling, digital/optical signal processing, nanotechnology, material science and technology, multifunctional technology, combustion processes, propulsion and flight physics, communication and networking, and computational and information sciences.
Questions about this opportunity? Please email ARLFellowship@orau.org