Location: Ann Arbor, MI Employment: Full- or part-time, in-person position Compensation: $20-$25 / hour US Citizenship required. Visto 360 AI is an Ann Arbor technology company that is revolutionizing radar Artificial Intelligence. Our team brings together radar scientists, AI engineers, software developers, and hardware specialists to solve challenging real-world problems at the intersection of sensing, machine learning, embedded systems, and signal processing. Visto360 AI is seeking a motivated Applied Mathematics / Computational Physics Intern to support research and development projects involving mathematical modeling, simulation, machine learning, sensor integration, robotics, and scientific software. This role is well suited for students interested in applying advanced mathematics, physics, numerical methods, and machine learning to real-world sensing and engineering problems. Interns will work with engineers and researchers on projects that may involve radar modeling, signal processing, sensor fusion, robotics integration, numerical simulation, ML experimentation, computational physics workflows, and analysis of complex datasets. Depending on background and project needs, work may include physics-based modeling, wave propagation, hydrodynamics-inspired methods, optimization, inverse problems, uncertainty analysis, or machine learning for scientific and engineering systems. Intern responsibilities may include: • Assist with applied mathematics, computational physics, robotics, and machine learning research projects. • Develop, test, and validate numerical algorithms using Python and scientific computing tools. • Support simulation, modeling, and analysis workflows involving radar, wave physics, signal processing, robotics, or related physical systems. • Contribute to sensor integration, sensor fusion, robotics workflows, and testing of real-world sensing systems. • Explore ML methods for scientific and engineering applications, including physics-informed models, surrogate models, data-driven simulation, or model evaluation. • Work with datasets from simulations, experiments, sensors, robots, radar systems, or engineering platforms. • Implement mathematical models, optimization routines, numerical solvers, or analysis scripts. • Help evaluate model performance, numerical stability, uncertainty, and computational efficiency. • Research emerging methods in applied mathematics, computational physics, machine learning, hydrodynamics, robotics, sensing, and scientific AI. • Document technical findings, summarize results, and present progress to engineers and researchers. • Collaborate with a multidisciplinary team across AI, radar, software, robotics, hardware, and research engineering. Preferred Qualifications: • Current student pursuing a degree in Mathematics, Applied Mathematics, Physics, Engineering Physics, Computer Science, Data Science, Electrical Engineering, Mechanical Engineering, Aerospace Engineering, Robotics, or a related STEM field. • Strong foundation in applied mathematics, physics, numerical methods, or scientific computing. • Python programming experience. • Experience with NumPy, SciPy, Matplotlib, Jupyter, PyTorch, TensorFlow, ROS, OpenCV, or similar tools. • Coursework, research, or project experience in one or more of the following areas: complex analysis; machine learning or deep learning; computational physics; numerical methods; partial differential equations; optimization; linear algebra; probability and statistics; signal processing; robotics or autonomous systems; sensor integration or sensor fusion; fluid dynamics or hydrodynamics; wave propagation; radar, acoustics, electromagnetics, or related sensing systems; scientific simulation or high-performance computing • Strong analytical and problem-solving skills. • Ability to work independently, learn new technical material quickly, and communicate results clearly. • Ability to work on-site with a technical team in Ann Arbor. Experience with any of the following is helpful but not required: • Complex analysis, harmonic analysis, Fourier analysis, or advanced mathematical methods used in physics and signal processing. • Robotics, embedded sensing platforms, sensor integration, sensor fusion, or field testing. • Physics-informed neural networks or scientific machine learning. • Surrogate modeling, reduced-order modeling, or differentiable simulation. • Computational fluid dynamics, hydrodynamics, turbulence modeling, or continuum mechanics. • Fourier methods, FFTs, spectral methods, finite difference methods, finite element methods, or numerical PDE solvers. • Radar concepts, SAR imagery, Doppler processing, wave scattering, or signal-processing algorithms. • Bayesian inference, uncertainty quantification, inverse problems, or statistical modeling. • ROS, robotics middleware, cameras, IMUs, LiDAR, radar, GPS, or other sensor systems. • GPU acceleration, CUDA, JAX, PyTorch, or high-performance scientific computing. • C/C++, Linux, Git, Docker, or reproducible research workflows. • Technical writing, research documentation, or experimental analysis. We are looking for interns who are mathematically strong, technically curious, and interested in applying computational methods to real-world sensing, robotics, and AI problems. The ideal candidate enjoys moving between theory, code, simulation, data, and physical systems, and is comfortable working on open-ended technical problems with a multidisciplinary engineering team. Job Type: Full-time Pay: $20.00 - $25.00 per hour Work Location: In person