What we're looking for from you:

• A degree or PhD in a related field, or a degree with a strong mathematical foundation and programming skills.
• Relevant experience (Post-Doctoral or industrial) in robotics, data fusion, tracking/estimation, pattern recognition, statistical inference, optimization, and machine/deep learning algorithms, along with real-time implementation, validation, and verification.
• Proficiency in tools like Matlab, Simulink, Stateflow, Python (including PyTorch, TensorFlow, Open AI-Gym/Universe), or Model-Based Design is desirable.

We encourage clients IAS Engineers to develop broad, in-depth knowledge across a variety of fields. Specific knowledge or experience in the following areas would be an advantage:

• Robotics, guidance, and autonomous decision-making, such as routing and motion/trajectory planning, optimization, coordinated guidance and control, decision theory, MDPs/POMDPs, specialist systems, game theory, decision support systems, and multi-agent systems.
• Data fusion and state estimation/tracking algorithms like Kalman Filtering, multiple-model tracking methods, particle filters, grid-based estimation, Multi-Object-Multi-Sensor Fusion, data association, random finite sets, Bayesian belief networks, and Dempster-Shafer theory of evidence.
• Machine Learning for regression, pattern recognition, and discovery, including Gaussian processes, latent variable methods, support vector machines, probabilistic/statistical models, neural networks, Bayesian inference, random forests, novelty detection, and clustering.
• Deep Learning such as Deep reinforcement learning, Monte-Carlo tree search, deep regression/classification, deep embeddings, recurrent networks, and natural language processing.
• Computer Vision algorithms, including structure from motion, image-based navigation, SLAM, and pose estimation/recovery.