The US Air Force Research Laboratory is seeking motivated candidates to perform research in the synthesis of carbon nanotubes. Our lab has developed 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 continue to expand and build upon the experimental capabilities and AI algorithms for ARES.

The research will involve implementation of new machine learning algorithms to understand and control carbon nanotube growth, with an emphasis on incorporating the physics and chemistry involved in the catalytic CVD process. The scientist is expected to work in close collaboration with software engineers and machine learning/Artificial Intelligence experts to advance carbon nanotube growth with controlled properties. This position requires expertise in catalysis, carbon nanotube growth, analytical techniques and electron microscopy. Experience with machine learning and programming is a plus. A successful candidate will be self-motivated and capable of working independently between multiple groups, while successfully collaborating with researchers from different technical backgrounds.

 

Requirements

• Ph.D. in Materials Science, Chemistry or related field of study is required • Background in chemical vapor deposition/catalysis 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

key words

Autonomous Research Systems; ARES (TM); Carbon nanotubes; Closed-loop research; Autonomy; AI/ML; Artificial Intelligence; Machine Learning; Computer methods; Software engineering; Catalysis

Citizenship:  Open to U.S. citizens

Level:  Open to Postdoctoral and Senior applicants