This program supports various projects within the Air Force Research Laboratory (AFRL) Sensors Directorate (AFRL/RY). AFRL/RY includes within its mission the improvement of Air Force intelligence, surveillance, and reconnaissance (ISR) capabilities, through both sensor device enhancements and novel processing of sensor data. The Air Force employs ISR information as a strategic element during peacetime, as a tactical enabler during conflict, and as a life-saver during emergencies and natural disasters. The goal of the Sensing, Learning, Autonomy, and Knowledge Engineering (SLAKE) program is to advance Air Force sensing capabilities by employing diverse sensor processing results at a representational or product level that is abstracted from the direct sensing output yet retains crucial information and corresponding uncertainties. Key research areas under SLAKE include Machine Learning (ML), Artificial Intelligence (AI), autonomous systems development, sensor product representations, sensor resource allocations, system architectures, and other mission support needs for AFRL/RY.
The goal of this effort is to support continued work on the creation and maintenance of algorithm and software development within Python that would allow analysts and researchers to understand adversarial behaviors for the Tracking and Fusion, and the Patterns of Life (PoL) teams, and incorporate the analyses into the Insight and Multi-Domain Analysis Development and Evaluation (MAD-E) architecture.
A candidate must meet the minimum qualifications listed below.