Dear ROS users,
for your attention (apologies for cross posting):

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