Assistant Project Scientist – California PATH - UC Berkeley
California PATH (http://www.path.berkeley.edu/) is a leading research organization on intelligent transportation systems, especially in the areas of vehicle automation. We are seeking qualified and passionate candidates to fill one position of researchers, with a title of Assistant Project Scientist.
The expected project duration is 12 months, full time appointment, with possible extension based on project needs. Anticipated start date: May or June 2018.
• Conduct research, development, and coding of new and existing algorithms, tools and technologies to enable leading edge scientific applications in AI, ML, and ADS. Within ADS, research topics may include sensing, detection, perception, mapping localization, trajectory planning, decision making, and driving policy.
• Conduct scientific and engineering research in the areas of transportation, traffic simulation, and data science.
• Work in a multidisciplinary team environment, that fosters interactions between advanced technologies (hardware, software, languages) and domain science teams (AI, ML, ADS, transportation, traffic, etc.)
• Work in a multidisciplinary team environment, that fosters interactions between advanced technologies
• Apply state-of-the-art Machine Learning algorithms to address ADS related problems.
• Author peer-reviewed publications and contribute to grant proposals.
Basic Qualifications (at the time of application):
• Ph.D. or equivalent in a Computer Science, Electrical Engineering, Mechanical Engineering, Transportation Engineering, or related field.
• At least two years of experience in AI/ML based studies in both vehicle engineering and transportation engineering fields.
• Experience in using and developing cutting edge software, and/or hardware prototypes for ADS in a research environment.
• Experience in both computer programming languages (e.g., Python, C/C++) and AI/ML development frameworks (e.g., CAFFE, TensorFlow).
• Coding experience in conducting traffic simulation software (e.g., SUMO) and developing simulation platforms with object-oriented programming language (e.g. Established record of peer reviewed publications in ADS and/or automotive applications.
• Demonstrated written and oral communication skills.
• Experience in supervising and leading research team efforts.
• Experience in applying reinforcement learning for ADS applications.
• Demonstrated creativity and ability to design, develop and implement state-of-the-art machine learning tools consistent with emerging technologies to solve complex ADS problems.
• Ability to think “out of the box” to combine multidiscipline solutions for conventional engineering problems.
For the full job description and to apply, please go to:
Position will remain open until filled.