NNAISENSE is committed to deploying robust, intelligent control solutions based on state-of-the-art reinforcement learning that leverages formal concepts from control theory. We are seeking experienced control system scientists to join our intelligent automation team. You will bridge machine learning and control theory research, and contribute to internal projects as well as high profile client applications.
Description
- Perform cutting-edge R&D in both control theory (MPC, non-linear control, optimal control) and machine learning
- Further the development of our core control code base
- Contribute to selected client projects
Minimum Qualifications
- 3+ years research experience in the field of automatic control theory and applications
- PhD/MSc in engineering, math, physics, or computer science
- Working knowledge of advanced control technology such as MPC
- Familiarity with system identification and modeling techniques for physical systems
- Strong mathematical background and coding skills
- Fluent in Python or Wolfram Mathematica
- Fluent in written and spoken English
Pluses
- Expertise in Bayesian inference and reinforcement learning
- Experience with (recurrent) neural networks
- Experience with optimization techniques and algorithms
- Knowledge of stochastic control theory
- Familiarity with C/C++
Contact
E-mail: jobs@nnaisense.com
Submit both your cover letter and resume in English, PDF format
