Data Mining Research Engineer – Active Learning
For over a century the name "Bosch" was associated with forward-looking technology and trailblazing inventions that have made history. This job focus is to research, develop and apply active learning methods in applications across Bosch business areas: automotive, healthcare, industrial.
Company: Bosch RTC
Location: Palo Alto, CA
Web: www.bosch.us/content/language1/html/rtc.htm
The Bosch Group manufactures and markets automotive OE and aftermarket products, industrial automation and mobile products, power tools and accessories, security technology, and packaging equipment.
For over a century the name "Bosch" has been associated with forward-looking technology and trailblazing inventions that have made history. Bosch does business all over the world and is active in the most wide-ranging sectors. The Bosch Research and Technology Center focuses on the following topics: ASIC design and MEMS technology; Energy conversion and energy storage technologies, modeling simulation and controls; Wireless Technologies; Internet Technologies; Algorithms for Robotics, Autonomous Systems and Data Mining; and User Interaction Technologies. By choice, we are an Equal Opportunity Employer committed to a diverse workforce.
Your responsibilities:
- Research, develop and apply active learning methods in applications across various Bosch business domains (automotive, healthcare, industrial)
- Collaborate with product management, marketing and engineering teams in Business Units to elicit & understand their requirement & challenges and develop potential solutions
- Stay current with latest research and technology ideas; share knowledge by clearly articulating results and ideas through papers, presentations to research staff, management, and key decision makers.
- Publish in relevant top journals and conferences, contribute to RB's patent portfolio
Your competencies and qualifications:
- Strong background in at least one of the following: active learning, budgeted learning, bandit mechanisms, or experimental design
- Strong programming experience in at least 2 of the following: Java, C++(STL), Python, Perl, Matlab, R, SPSS/SAS
- Needs a Ph.D. or M.S. with at least 3 years of relevant work experience (Computer Science, Statistics, or related field)
- Demonstrated ability to work both independently and within a team environment
- Experience in Bayesian adaptive designs (desired)
- Experience in validation of large scale machine learning systems (desired)
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