**Job Description**
The Research Assistant Scientist will focus on developing new abstractions and algorithms using computational sheaf theory. This includes creating algorithms for understanding composite energy-driven systems for both learning and dynamical systems, and new approaches to online learning of optimal policies for hierarchical cyber-physical systems by integrating learning and physics components. The role involves ideation, mathematical development, Lyapunov-based analysis, conducting simulations and experiments, disseminating research findings, leading some research efforts, and mentoring doctoral students in collaborative research.
**Skills & Abilities**
• Strong background in nonlinear (Lyapunov-based) analysis tools.
• Strong background in sheaf theory.
• Strong background in applied category theory.
• Software skills, including familiarity with high-performance computing.
• Strong writing and communication skills.
**Qualifications**
Required Degree(s) in:
• Mathematics
• Electrical Engineering
• Mechanical Engineering
• Closely related field
**Experience**
Other:
• Provide an official transcript to the hiring department upon hire.
• Degrees earned from an educational institution outside of the United States are required to be evaluated by a professional credentialing service provider approved by National Association of Credential Evaluation Services (NACES).
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