Conferences

PHM16

Denver, Colorado
Oct 2 - Oct 6, 2016


Key Dates

  • Abstract Due: 15 Apr 2016 13 May 2016
  • Doctoral Symposium Proposals: May 09, 2016 May 20, 2016
  • Paper Submission Due: 13 May 2016 10 June 2016
  • Technology Demos proposals: June 10, 2016
  • Panel Session proposals: June 03, 2016
  • Paper Review Feedback: July 15, 2016
  • Final Papers Due: August 05, 2016
A System-Based Approach to Monitoring the Performance of a Human Neuromusculoskeletal System
Marcus Musselman, Deanna Gates, Dragan Djurdjanovic    Read
An Inference-based Prognostic Framework for Health Management of Automotive Systems
Chaitanya Sankavaram, Anuradha Kodali, Krishna Pattipati, Satnam Singh, Yilu Zhang, Mutasim Salman    Read
PHM-Based Wind Turbine Maintenance Optimization Using Real Options
Xin Lei, Peter A. Sandborn    Read
A Probabilistic Machine Learning Approach to Detect Industrial Plant Faults
Wei Xiao    Read
  

We’re working on the future. If you are seeking an iterative fast-paced environment where you can drive innovation, apply state-of-the-art technologies to solve extreme-scale real world delivery challenges, and provide visible benefit to end-users, this is your opportunity.

Come work on the Amazon Prime Air Team!

The Prime Air team is seeking a Sr. leader of Reliability Engineering to develop and administer the vehicle and mission-specific hardware reliability programs. Activities within these programs include:
- Reliability models and budgets
- Component failure prognostics

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Company: 
Palo Alto Research Center (PARC, a Xerox Company)
Date Posted: 
April 27, 2016

Research position in system modeling with applications in model-based design, reasoning, diagnosis and prognosis.

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Company: 
Palo Alto Research Center (PARC, a Xerox Company)
Date Posted: 
January 4, 2016

Exciting internship opportunities available at PARC in system failure modeling, prognostics and health management.

  
Company: 
Palo Alto Research Center (PARC, a Xerox Company)
Date Posted: 
January 4, 2016

PARC is seeking an applied research scientist in prognostics, systems health management, data analytics, machine learning, control systems, or related fields to join a team of researchers developing innovative device fleet management systems. The focus area is automated predictive analytics based on transactional, image, machine logs, and other modality data streams from a fleet of complex electromechanical devices/systems.

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