Bosch R&D in Palo Alto, California, USA is looking for excellent candidates with expertise in probabilistic planning under uncertainty and decision making for a position in the automated driving team.
Degree Level: M.S. with at least 3 years of prior experience or Ph.D.
Major(s): Computer Science, Engineering, or a related field.
Your Duties and Tasks:
Perform research, develop, implement and evaluate algorithms in one or more of the following fields:
- Planning under uncertainty, probabilistic approaches in robotics as it is applicable to decision making for automated/autonomous vehicles
- Machine learning techniques for novel driver assistance applications or vehicle data analytics
- Novel ways for vehicle decision making, including methods like Bayesian risk analysis in uncertain environments
Skills / Job Requirements:
- Excellent knowledge and proven expertise in Planning under uncertainty/Probabilistic approaches in robotics
- Working knowledge of recent machine learning algorithms (Bayesian inference, (PO)MDP planning, etc.) as well as optimization techniques
- Excellent C++ programming expertise required, Python programming is a plus
- Proven system integration and software architecture skills
- Knowledge of Linux, and development on Linux systems preferred
- The ability to develop, understand and implement complex algorithms efficiently and correctly
- Experience with modern software engineering tools
- Experience working independently in a large software setting
- Experience working on robot and/or automotive electronics hardware a plus, as is experience with simulation environments and ROS
- Excellent communication skills and demonstrate a proven ability to multitask and deliver on challenging software development tasks
Details and Online Application:
http://www.bosch.us/content/language1/html/11706.htm
Thomas Glaser
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