Open PhD Position (Fault Detection with Data-Driven Models)
The Department of Knowledge-based Mathematical Systems’ at the Johannes Kepler University Linz is offering a PhD position in the field of fault detection and diagnosis with data-driven process models based on system identification, soft computing and machine learning techniques.
The basic task is to enhance the currently available techniques with new (data-driven) learning algorithms for process models (with improved predictive quality) and an advanced generation and analysis of fault indicators in order to detect various type of faults as early as possible and
furthermore to significantly improve the quality of machines and products.
The models should be developed for a range of processes from industry, where measurement data with various characteristics is recorded and supervised, ranging from stationary to dynamic data (time delays), including low-dimensional to high-dimensional variable spaces as well as containing un-labeled and labeled data.
Profile/Personal Qualification of the candidate:
Ideally, the candidate should have a completed master in Mathematics/Mechatronics/Informatics or other technical study and already have some knowledge about data-driven modeling, system identification as well as machine learning techniques. Interest in fault detection and diagnosis is warmly welcome.
Duration contract: 3 years
Start Date: as soon as possible
Approx. Salary (Gross): approx.35000-40000 Euro per Year (to be negotiated)
Finance: the position is financed within the ACCM strategic collaboration and the Department of Knowledge-Based Mathematical Systems/FLLL at the Johannes Kepler University Linz.
Contact: The candidate should send hisCV, degree certificates, references to publications etc.
(no later than 31st of July 2011) to
Dr. Edwin Lughofer, email: email@example.com Tel.: +43 (0)7236 3343 435
Applications from women are particularly encouraged.
Candidates must be allowed to work within the European Union (EU).