Internships at Mobius Logic, Inc

The future of automation increasingly appears to consist of hybrid teams of humans, foundation models (LLMs, Diffusion Models), and multi-agent semiautonomous onboard agents acting together to achieve a common series of goals. This hybrid environment requires humans to communicate commands and intentions to agents with the potential for discontinuous communication, split-second decision making, and goal reorientation of an entire team of autonomous agents with only minimal input from a commanding user. 
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Recently, we have been developing hierarchical, human-on-the-loop control systems for close proximity satellite operations and are now expanding this research into teams of autonomous agents acting collaboratively with human and non-human systems. We have developed open-ended, skill-based RL training methods that produce fleets of diverse, controllable agents, and are developing the systems and language for humans to effectively interact with these fleets in a semi-autonomous way. There are several projects available to interested interns in this pipeline including: training low level agents using reinforcement learning, developing algorithms for dynamic teaming, course of action generation and human interpretable skill-based planning, and evaluation of multilayered highbred RL/control/OR systems.
 
The chosen interns will be part of a team of other members with varied skills in Data Science, NLP, Mathematics, and Software Development.  During the internship, the interns will learn and code in Python, integrate their work with the compute platform, make changes to the Mobius Logic DRL engines, attend weekly meetings with project members, read and discuss papers, present their work, and write research reports.