Multi-Source Data Fusion Research Associate Full-time NEW

Multi-Source Data Fusion Research Associate

Applied Research Laboratories is a University Affiliated Research Center at The University of Texas at Austin, located on the Pickle Research Campus in North Austin. Through fundamental research, innovative science, and applied engineering, ARL:UT makes significant contributions in support of national security.

Within ARL:UT, the Space and Geophysics Laboratory (SGL) engages in research in electromagnetic propagation, geo-positioning, and remote sensing. The lab monitors the long-term performance of GPS, addresses the specification of government geodetic-quality GPS receivers, and designs and executes government tests for industry-produced receivers.

We are seeking a Research Associate to provide multi-source data fusion, environmental and geospatial modeling, and machine learning expertise and scientific rigor across a portfolio of technologies germane to interests of SGL listed above in order to effect improvements to these interests and advance the state-of-the-art in these areas. The successful candidate will support the design, development, and independent evaluation of multi-source data fusion, environmental modeling, and digital twin / multi-agent simulation capabilities, including object detection, classification and tracking, route prediction, and decision support functions.

Responsibilities include:

• 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.
• Contribute to the first principles problem formulations, algorithm development, systems designs, and software implementations for specialized data fusion and modeling applications.
• 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.

Required Qualifications

• PhD in engineering, computer science, computational science, physics, mathematics, oceanographic science, earth science, geospatial science, or related discipline.
• Experience developing software for scientific applications.
• Experience developing data fusion, statistical estimation, machine learning, or environmental/geospatial modeling algorithms.
• Demonstrated record of authoring peer-reviewed scientific publications.
• Demonstrated record of presenting scientific content to technical and non-technical audiences.

Applicant must have a dynamic skill set, willing to work with new technologies, be highly organized and capable of planning and coordinating multiple tasks and managing their time. The position will require attention to detail, effective problem solving skills and excellent judgment. Ability to work independently with sensitive and confidential information, maintain a professional demeanor, work as a team member without daily supervision and effectively communicate with various groups of clients. Able to work under pressure and accept supervision. Regular and punctual attendance.

US Citizen. Applicant selected will be subject to a government security investigation and must meet eligibility requirements for access to classified information at the level appropriate to the project requirements of the position.

Preferred Qualifications

• Experience developing and evaluating multi-source data fusion systems, including detection, correlation, and classification refinement.
• Experience with object detection, classification, and tracking using various data sources.
• Experience developing and applying environmental models (e.g., oceanographic, meteorological, terrain, bathymetric) for prediction, simulation, and suitability analysis.
• Experience applying machine learning to detection, classification, and prediction problems.
• Experience with digital twin architectures, agent-based modeling, and simulation of operational courses of action.
• Experience with route prediction, behavior modeling, and movement pattern analysis.
• Experience designing, implementing, and deploying robust scientific software.
• Experience employing statistical estimation techniques.
• Experience with high-performance computing.
• Experience with geospatial data processing and Geographic Information Systems (GIS) tools.
• Eligibility for immediate access to classified information.
• Experience in writing proposals for and leading externally-funded research projects.
• Proficiency with programming languages such as Python, C/C++, FORTRAN, or similar.
• Experience developing on Linux and Windows platforms, including terminal-based environments (bash), version control (Git and GitHub/GitLab), and cloud services (such as AWS).
• Proficiency with LaTeX.
• Minimum cumulative GPA of 3.0.

Salary Range

$120,000-$165,000+/negotiable depending on qualifications

Working Conditions

• Standard office conditions
• Repetitive use of a keyboard at a workstation
• Use of manual dexterity
• Some weekend, evening and holiday work
• Possible interstate/intrastate travel

Required Materials

• Resume/CV
• 3 work references with their contact information; at least one reference should be from a supervisor
• Letter of interest
• Unofficial college transcripts