Senior Research Associate: Aerospace Engineering Autonomy

Senior Research Associate:
Aerospace Engineering Autonomy

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Aerospace Engineering Autonomy role at San José State University Research Foundation

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Aerospace Engineering Autonomy role at San José State University Research Foundation

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The San José State University Research Foundation (SJSURF) is committed to building a work environment where everyone can show up as their own self and have an opportunity to contribute, develop, and advance in their career. Diversity, Equity, and Inclusion (DEI) are core values of the organization. We strive to attract, retain, and develop employees who reflect the community and society where we work and live.

The Research Foundation aims to develop a culture where everyone feels welcome, shares their views, and where differences in backgrounds and perspectives are seen as adding value.

The Psychology Department at San Jose State University is involved in collaborative research efforts with civil service scientists from the U.S. Army’s Technology Development Directorate (TDD) Research Group at the NASA Ames Research Center in Mountain View, CA. This is a journeyman-level engineering position with the TDD focused on Autonomy as it relates to the U.S. Army’s Future Vertical Lift (FVL) and Contested Logistics (CL) modernization priorities.

The work is centered on research and development efforts of rotorcraft flight control technologies and operations for both manned and unmanned systems and optionally piloted air‑vehicles.

• Develop advanced autonomy algorithms applicable to fully autonomous flight and optionally piloted operations.
• Serve as the principal investigator in the planning, execution, data reduction, and reporting of flight test experiments that exercise, demonstrate, and increase the technology readiness level of autonomy algorithms.
• Develop and demonstrate active and passive perception techniques for terrain‑aware helicopter motion planning.
• Design and evaluate methods for fusing data from a range of terrain sensors that account for atmospheric effects and sensor degradation.
• Research machine learning techniques suitable for real‑time segmentation and classification of landing surfaces based on active and passive sensing.
• Develop methods of incorporating real‑time changes in dynamic envelope and atmospheric effects into autonomous motion planning for helicopter terrain flight.
• Become familiar with the Army’s Mission Adaptive Autonomy (MAA) software.
• Become familiar with the Army’s flight controls and system identification tools, including CIFER, CONDUIT, STITCH, and RIPTIDE.
• Attend weekly group meetings and present research updates.
• Effectively communicate research results through technical presentations and written reports.
• Other duties as assigned.

Reports to the Project Director. Interacts with Foundation research staff and civil service staff on a daily basis via telephone, email, Teams, and/or in‑person. Working onsite at Ames is required 3 days per week. Telework from an approved location is permitted.

Education and Experience

• MS in Aerospace Engineering or related field required.
• Education in the following areas:
  Machine learning; numerical analysis and statistical methods, flight dynamics and control; aircraft simulation; classical and optimal control; linear control theory; MATLAB, Simulink, Python.
• Experience in an applied research setting is highly desired.

Knowledge, Skills, And Abilities Required

• Strong verbal and written communication skills.
• Ability to work on collaborative teams or independently.
• Demonstrated ability to conduct independent research.
• General knowledge of flight control and fixed/rotary wing aircraft and unmanned aerial system (UAS) controls.
• General knowledge in machine learning‑based optimization methods.
• Experience in autonomous UAS waypoint navigation, simultaneous localization and mapping (SLAM), and image recognition.
• Demonstrated strong…