Conferences

PHM16

Denver, Colorado
Oct 3 - 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 July 31, 2016
  • Final Papers Due: August 5, 2016 August 15, 2016
Big data analytics in online structural health monitoring
Guowei Cai, Sankaran Mahadevan    Read
Prognostics of Combustion Instabilities from Hi-speed Flame Video using A Deep Convolutional Selective Autoencoder
   Read
Temporal Learning in Video Data using Deep Learning and Gaussian Processes
Devesh K. Jha, Abhishek Srivastav, Asok Ray    Read
Wearable EEG-based Activity Recognition in PHM-related Service Environment via Deep Learning
Soumalya Sarkar, Kishore Reddy, Alex Dorgan, Cali Fidopiastis, Michael Giering    Read
  

Do you love machine learning and data analytics? Do you dream about new regression algorithms?

We’re currently implementing the art of the possible in prognostics, diagnostics, anomaly detection, optimization and more ‘run of the mill’ analytics. It certainly aint easy.

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The nano-Macro Reliability Lab (nMRL)at the Singapore University of Technology and Design (SUTD) is offering multiple Ph.D. scholarships for highly qualified candidates in the field of prognostics and system health management (PHM). Selected candidates should have relevant backgrounds in applied mathematics/statistics and be interested in applying different mathematical tools and techniques for real-time lifecycle prediction of engineering devices and systems, in general.

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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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