Conferences

PHMAP17

Jeju, Korea
Jul 12 - Jul 15, 2017


Key Dates

  • Abstract Due: 20 January, 2017 10 February, 2017
  • Short or Full Paper Submission Due: 24 February, 2017
  • Paper Review Feedback: 21 April, 2017
  • Final Papers Due: 19 May, 2017
  • Pre-registration Due: 19 May, 2017

PHM17

St. Petersburg, Florida
Oct 2 - Oct 5, 2017

Key Dates

  • Abstract Due: 21 April 2017 12 May 2017
  • Doctoral Symposium Proposals: 8 May 2017
  • Paper Submission Due: 19 May 2017 2 June 2017
  • Technology Demos proposals: 9 June 2017
  • Paper Review Feedback: 14 July 2017
  • Final Papers Due: 4 August 2017
Condition Based Maintenance of Low Speed Rolling Element Bearings using Hidden Markov Model
Guru Prakash, Sriram Narasimhan, Mahesh Pandey    Read
An Integrated Architecture for Corrosion Monitoring and Testing, Data Mining, Modeling, and Diagnostics/Prognostics
Honglei Li, Margaret R. Garvan, Jiaming Li, Javier Echauz, Douglas W. Brown, George J. Vachtsevanos, Frank Zahiri    Read
A Bayesian approach to fault identification in the presence of multi-component degradation
Yufei Lin, Skaf Zakwan, Ian Jennions    Read
Feature Selection for Monitoring Erosive Cavitation on a Hydroturbine
Seth W. Gregg, John P.H. Steele, Douglas L. Van Bossuyt    Read
  
Company: 
Lockheed Martin
Date Posted: 
April 26, 2017
Contact: 
Roni Hendrickson - Roni.Hendrickson@lmco.com

Job Description
• Primary role is advanced member of the F-35 Prognostics & Health Management (PHM) Capability Integration Team as the Data Analytics Integrator.
• Primary responsibility is to lead the maturing of the F-35 PHM capability by understanding the aircraft systems/subsystems design, PHM design, actual PHM performance, and developing required corrective actions and automating team tools to improve efficiencies.

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Company: 
ALSTOM
Date Posted: 
April 19, 2017
Contact: 
diego.tobon@alstom.com or bertrand.chauchat@alstom.com

We are looking for a PhD who has defended his/her thesis in the domain of fault detection, diagnostics and/or prognostics. In addition to these latter skills, the candidate should have strong knowledge in electrical engineering (electrical machines) and signal processing. He/she has also to be good in setting experimental test benches (hardware and software) and possesses skills in programming (Matlab and Labview). Finally, the candidate should speak English fluently, intermediate French speaking would be appreciated.

1. Objective of the study

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Company: 
NIO
Date Posted: 
April 12, 2017

NIO, the maker of the world's fastest electric car, the EP9, is developing electric autonomous cars that will revolutionize the user experience. Join the Data Science team that underpins this vision by using data combined with physics/math/statistics and machine learning to develop algorithms for both personalization and logistics.

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We are looking for the right people — people who want to innovate, achieve, grow and lead. We attract and retain the best talent by investing in our employees and empowering them to develop themselves and their careers. Experience the challenges, rewards and opportunity of working for one of the world’s largest providers of products and services to the global energy industry.

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You set up research projects with top companies in Flanders to develop autonomous machines, robots and vehicles. You and your team execute the projects by modeling the system design, the controller and testing and validating the autonomous systems in the brand new lab infrastructure.

Flanders Make researchers help manufacturing companies in making high-performance, flexible and autonomous machines, robots and vehicles, f.e. by rethinking the entire system architecture using a variety of (beyond) state-of-the art technologies.

Develop intelligent, self-learning supervisory controllers

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