Multi-Source Data Fusion Research Associate

The University of Texas at Austin is hiring a Multi-Source Data Fusion Research Associate for its Applied Research Laboratories. The role conducts and advances research in data fusion, environmental and geospatial modeling, machine learning, and digital twin and multi-agent simulation, including developing, evaluating, and implementing related algorithms and software.

Responsibilities:

• Perform high-level independent research in multi-source data fusion, environmental and geospatial modeling, machine learning, and digital twin / multi-agent simulation relevant to the interests of SGL
• Present and publish your research, both internally and externally. This may involve participating in project reviews and technical interface meetings to present designs and test results to sponsors and other external organizations, as well as publishing work in scientific journals and presenting work at conferences
• Contribute to the first principles problem formulations, algorithm development, systems designs, and software implementations for specialized data fusion and modeling applications, employing expertise in statistical estimation, geospatial and environmental modeling, machine learning, and sensor phenomenology
• Develop multi-source data fusion algorithms to improve detection, correlation, and classification
• Develop environmental suitability models to predict routes and movement patterns and to simulate courses of action
• Contribute to digital twin and multi-agent simulation capabilities that synthesize historical patterns, environmental models, and activity data to generate predictions, identify areas of interest, and support decision making
• Design experiments and corresponding analyses to gauge the performance of fusion, object classification and tracking, route prediction, and decision support methods, and develop recommendations to effect improvements
• Implement software algorithms in a collaborative environment. Work closely with team members to define interfaces between program components. Document implementations thoroughly and clearly. Define, implement, and execute test cases for program functions
• Further develop knowledge of multi-source data fusion, statistical estimation, machine learning, environmental modeling, and software development principles
• Provide guidance and assistance to other full time employees and student employees
• Provide technical leadership and identify new directions for research
• Other related functions as assigned and occasional travel to support meetings