opportunity |
location |
|
13.25.04.C0441 |
Wright-Patterson AFB, OH 454337817 |
name |
email |
phone |
|
Benji Maruyama |
benji.maruyama@afrl.af.mil |
937.255.0042 |
The US Air Force Research Laboratory is seeking motivated candidates to expand the capabilities of ARES™, the Autonomous Research System at AFRL. ARES™ is the first of its kind fully autonomous research robot that uses AI to learn to grow carbon nanotubes by closed-loop iterative experimentation [1, 2]. We are expanding and building upon the experimental capabilities and AI algorithms for ARES to include additive manufacturing/3D printing and flow chemistry, among others. We are also studying human-machine teaming through synthetic agent development and cognitive psychology.
We seek a broad range of talented researchers for the multi-disciplinary team to include materials science or related areas, autonomy/robotics, computer science/software engineering, human-machine interactions, artificial intelligence/machine learning, operations research/applied mathematics/industrial or systems engineering, symbolic regression/knowledge representation, and decision science/optimal experimental design.
One current area is the expansion of the current additive manufacturing ARES™ system (AM ARES) to incorporate rheological and prior knowledge of AM systems into the decision-making loop. Concurrently we seek to make our AM ARES system accessible online via open source software, data and decision tools, with the goal of making AM ARES affordable and educational.
The autonomous research area is rapidly expanding and developing, and so interested candidates are encouraged to reach out to the PI for current investments.
Requirements
• Ph.D. in Materials Science, Chemistry or related field of study is required for the materials researcher role. Alternatively, a Ph.D. in areas related to autonomy/robotics, computer science/software engineering, human-machine interactions, artificial intelligence/machine learning, operations research/applied mathematics/industrial or systems engineering, symbolic regression/knowledge representation or decision science/optimal experimental design is required
• Excellent oral and written communication skills are a prerequisite for employment
• This position is working within a government facility and requires U.S. Citizenship
References
1. Nikolaev et al., NPJ Computational Materials (2016) 2, 16031
2. D. Tabor et al. Nat. Rev. Mater. 3, 5-20, 2018
3. Reyes, Kristofer G., and Benji Maruyama. MRS Bulletin 44.7 (2019): 530-537.
Autonomous Research Systems; ARES (TM); Closed-loop research; Autonomy; AI/ML; Artificial Intelligence; Machine Learning; Computer methods; Software engineering; symbolic regression; human-machine interface; additive manufacturing; 3D printing; flow chemistry; decision science