What are the responsibilities and job description for the Uncertainty-Aware AI&ML for Information Fusion position at Zintellect?
About the Research
Information fusion systems to meet future Army challenges will require advanced AI&ML technology that can learn and make inferences over sparse, conflicting, and heterogeneous data from possibly unreliable information sources. Currently, AI&ML systems can achieve high performance under “normal” conditions for which they were trained. However, the quality of their inferences degrade rapidly as conditions change. Furthermore, AI&ML systems have high vulnerability to adversarial attacks. It is crucial to advance AI&ML technology so that it can properly express uncertainty in its inferences and identify the “unusual” observations and corresponding reasoning path to the user to achieve more robust decision making. Recent advances in Bayesian and evidential neural networks, second-order probabilities, trust/reputation systems, and subjective logic appear to provide a pathway to achieve such uncertainty-awareness. This project seeks further research in these areas.
ARL Advisor: Lance Kaplan
ARL Advisor Email: lance.m.kaplan.civ@mail.mil
About SEDD
The Sensors and Electron Devices Directorate (SEDD) is the Army’s principal center for research and development in the exploration and exploitation of the electromagnetic spectrum, which includes radio frequency, microwave, millimeter-wave, infrared (IR), visible, and audio regions. SEDD is responsible for advances in laser sources, RF sources, IR sensors, signature detection and decoding, target imaging and its interpretation, fusion of data derived from several sensors, and electromagnetic protection.
In addition, SEDD is responsible for improving the technology base for electron devices and materials related to sensors and power devices. Research is conducted in related aspects of physics, electrical engineering, computer science, solid-state physics, chemical engineering, material sciences, and electrochemistry.
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.
A complete application includes:
- Curriculum Vitae or Resume
- Three References Forms
- An email with a link to the reference form will be available in Zintellect to the applicant upon completion of the on-line application. Please send this email to persons you have selected to complete a reference.
- References should be from persons familiar with your educational and professional qualifications (include your thesis or dissertation advisor, if applicable)
- Transcripts
- Transcript verifying receipt of degree must be submitted with the application. Student/unofficial copy is acceptable
If selected by an advisor the participant will also be required to write a research proposal to submit to the ARL-RAP review panel for :
- Research topic should relate to a specific opportunity at ARL (see Research Areas)
- The objective of the research topic should be clear and have a defined outcome
- Explain the direction you plan to pursue
- Include expected period for completing the study
- Include a brief background such as preparation and motivation for the research
- References of published efforts may be used to improve the proposal
A link to upload the proposal will be provided to the applicant once the advisor has made their selection.
Questions about this opportunity? Please email ARLFellowship@orau.org
