Probabilistic Inference for Fleet Management Applications: Global industries, ranging from automotive to publishing, from heavy equipment to medical devices, face the challenge of deploying, monitoring, and maintaining fleets ranging from thousands to millions of diverse assets spread around the world. In the Embedded Reasoning Area at PARC, we are engaged in creating integrated platforms that leverage advanced sensing, model-based reasoning and statistical inference methods to allow fleet managers to understand the state of their fleets, isolate difficult to resolve problems arising in the field, predict future needs for capacity and maintenance, and make effective decisions about how to allocate resources to meet these needs. PARC is seeking an experienced applied research scientist with expertise in probabilistic inference. The ideal candidate would have experience in application areas such as diagnostics, prognostics, modeling of physical systems, large-scale inference, data analysis, machine learning, or related fields. Desired prior experience includes developing novel solutions in sensor interpretation, anomaly detection, fault detection, remote diagnosis, and remaining useful life estimation. The candidate will work with leading companies from around the world and face challenges in representing and reasoning about complex systems and analyzing large volumes of data. The successful candidate will be part of a multidisciplinary team with expertise in automated planning, scheduling, hardware design, probabilistic inference, optimization, machine learning, advanced materials, and sensing. The team is supported by specialists with expertise in networked, web-based, parallelized and cloud computing platforms, and hardware expertise in electronic and materials design. Opportunities to develop new projects, attend top international conferences, and be part of spin out companies are a part of PARC culture. The ideal candidate is a self-starter who can communicate with customers, elicit requirements, define and refine application concepts, and lead development teams to take ideas from the drawing board to prototype deployment. We are looking for someone with demonstrated leadership skills. This is NOT a fundamental research position. We are only looking for candidates who are interested in delivering results based on cutting-edge diagnostics, prognostics, data analysis, and machine learning methods. Responsibilities:
* Work with stakeholders to understand customer needs for fleet management and turn them into concrete requirements. * Design, develop, and deliver innovative approaches, methods, and algorithms, as needed. * Make "buy-versus-build" decisions for platform software and hardware capabilities. * Design and lead the development of software prototypes. * Lead efforts to engage new customers and to develop new business opportunities, including proposal development. Requirements: * Ph.D. in Computer Science, Electrical Engineering, Mechanical Engineering, or related disciplines * At least five years of experience in applied R&D (preferably in a commercial or government laboratory setting) * Demonstrated expertise in probabilistic inference, diagnosis, prognostics, modeling, statistics or machine learning Other desired competencies: * Experience managing research or development teams * Experience with fleet management applications * Track record in raising research & development funding * Demonstrated business development skills Application: Please see the following link for details and directions for applicants: * Parc culture: http://www.parc.com/about/culture.html * Job Position: http://www.parc.com/job/103/member-of-research-staff.html
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