Engineering Physics Summer Internship- Machine Learning

The Air Force Institute of Technology is looking for 2025 candidates to participate in a paid summer internship for 10-12 weeks at Wright Patterson Air Force Base (Dayton, Ohio). This Internship is in the Engineering Physics Department, with the Center for Directed Energy. All applicants must be U.S Citizens and be able to pass a background check. 

Project Title: Use of machine learning algorithm predicting soil heat fluxes (SHFs) for energy budgeting and computing optical turbulence structure function (Cn2) for directed energy applications

Project Description: Machine learning algorithms have become pivotal in accurately predicting soil heat fluxes (SHFs), a critical parameter in energy budgeting. By analyzing patterns in environmental data, these algorithms provide precise estimations of SHFs, accounting for complex interactions among soil properties, temperature gradients, and moisture levels. Accurate SHF predictions are essential for computing the optical turbulence structure function, Cn2​, which quantifies atmospheric refractive index variations affecting directed energy systems. Incorporating SHFs into Cn2​ calculations enhances the modeling of energy propagation in various environmental conditions, optimizing the performance of directed energy applications like laser communication and targeting systems. Machine learning facilitates real-time adaptation, offering robust solutions for dynamic scenarios. An incumbent will have field work, lab work, and table work for writing a report and making a presentation.

Majors: Any STEM