Ph.D. in Machine Learning (The Netherlands) Deadline: June 09, 2019

Eindhoven University of Technology

Application Deadline

June 09, 2019

Program Commencement

September 01, 2019

Duration of the Program

4 Years

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Program Details

The School of Industrial Engineering of Eindhoven University of Technology (TU/e) invites applications for a PhD position in the area of Explainable Machine Learning for Preventing Machine Breakdown.

Eindhoven University of Technology, one of the world’s leading research universities, is in particular well‐known for its joint research with industry. The Information Systems Group in the School of Industrial Engineering performs advanced research in the area of business process engineering, focusing on business process management (BPM) and business process intelligence (BPI). The group has a strong national and international reputation for both basic research in the academic community and applied research with industry. The successful applicant will have the opportunity to profit from the benefits that such an environment has to offer and to contribute to the ongoing research.

Modern manufacturing employs new levels of information technology addressing domains such as big data, AI, machine learning and decision support. The amount of data that is generated during the execution of a production process is growing. For instance, manufacturing machines are equipped with sensors that gather a lot of information about the production process. As a consequence, it is increasingly hard to extract useful information from a large amount of data that is produced. Linguistic summarization helps to point business analysts in the direction of useful information, by verbalizing interesting patterns that exist in the data.

For industry, temporal anomaly detection within production processes can be useful as such temporal patterns can indicate relationships between machine breakdowns and their causes. Understanding and explaining those patterns provides the industry with important information on the potential for increasing the uptime of their machines.

The main objective of this Ph.D. project is to research, design and develop concepts, techniques and prototype technologies for detecting temporal dependencies within manufacturing process data. Explainability of why machine breakdowns happen is one of the main application areas of the project. This approach is in line with cutting-edge research on Explainable AI.

The job offers:

  • a challenging job in a dynamic and ambitious university;
  • a PhD appointment for a period of 4 years;
  • gross monthly salary is € 2325- in the first year up to  € 2971,-  (gross) in the fourth year (on a full-time basis);
  • a yearly holiday allowance of 8% and 8.3% end of year allowance;
  • a broad package of fringe benefits (including an excellent technical infrastructure, moving expenses, savings schemes, coverage of costs of publishing the dissertation and excellent sports facilities).

Eligibility/ Requirements

The applicant should have a Master’s degree in Computer Science, Data Science, Industrial Engineering, or a similar field of study. The should have a strong interest in interdisciplinary research and collaboration with industry. Candidates with a strong and verifiable background in programming are preferred. The candidates should be able to work on a challenging topic that has both basic and applied research aspects. The candidate is expected to have excellent communication skills and proficiency in English and be able to collaborate in an international setting.

Application Process

Apply for the position here.

The application must contain the following documents:

  • cover letter (1-page max), which includes a motivation of your interest in the vacancy and an explanation of why you would fit well for the project;
  • a detailed curriculum vitae;
  • a course list of your Masters and Bachelor programs (including grades);
  • results of a recent English language test, or other evidence of your English language capabilities;
  • name and contact information of two references.

More information about the IS group can be found here. Questions about this position can be addressed to dr. Anna Wilbik (a.m.wilbik[at]tue.nl). Information about terms of employment can be obtained from Susan Opgenoorth, personnel officer (pz.ieis[at]tue.nl ). Further information about the Eindhoven University of Technology and the program can be found here.

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