The position focuses on bringing machine learning techniques to real-world decision making problems. It has a strong emphasis on real problems with real solutions and requires broad knowledge in the areas such as reinforcement learning, deep learning and policy optimization.
- Perform research to make machine learning applicable to real world decision making problems.
- Develop decision making and motion planning algorithms for autonomous vehicles.
- Participate in software development and prototyping.
- Contribute to a portfolio of patents and academic publications demonstrate research value.
- PhD/MSc in Computer Science, Electrical Engineering, or related field.
- Expertise in machine learning.
- Expertise in decision making under uncertainty.
- Familiarity with motion planning algorithms.
- Proven track record in conferences/journals.
- Strong programming skills in Python or C++.
- Experience in reinforcement learning and/or deep learning.
- Experience in behavior cloning.
- Familiarity with probabilistic reasoning in AI.
- Experience in deep learning frameworks such as Tensorflow.
- Familiarity with Robot Operating System (ROS).