PostDoc in the field of Machine Learning

 


Daytime stands for Digital Lifecycle Twins for Predictive Maintenance. The objective of the Daytime `project is to demonstrate the applicability of Industry 4.0 and in particular DayTime innovations beyond traditional productions plants into the hospitals and the home by treating healthcare equipment as means or tools for production.

Healthcare encompasses both capital intensive equipment in hospitals and smart consumer products at homes. In either case reliable mapping of user interaction into system response is crucial in supporting the customer to optimally operate the product. DayTime will enable manufacturers to transform into digital service provides giving advice tailored to the user. This advice will be based on actual system status and usage combining digital twin concepts with user/usage profiling. The advice encompasses suggestions to improve performance, reduce wear and tear and provide instructions to improve longevity or pro-actively deliver maintenance as service.

The TU/e will focus on knowledge valorization by creating and translating research results into successful innovations, working together with the consortium partners, especially with Philips Research and Philips Magnetic Resonance business on the topics of predictive and reactive maintenance by applying data science and artificial intelligence technologies.

An extensive project description is available on request.

TASKS of the post-doctoral researcher:

  • carry out research within the project, in cooperation with the other parties involved;
  • report on the results in project deliverables, papers and conference contributions;
  • a small contribution to the teaching activities of the Computer Science Faculty may be asked.

Job requirements

We are looking for a candidate who meets the following requirements:

  • A PhD degree in computer science, information science or related fields (mathematics or electrical engineering);
  • A research oriented attitude;
  • Solid publication record and accomplishments in machine learning and or artificial intelligence
  • Knowledge and practical experience in at least one of the following areas: NLP, text mining, machine learning, and knowledge management
  • Solid programing skills (e.g. Java)
  • Knowledge of Phyton, R Tensorflow, and/or similar languages/tools;
  • Ability to work in a team, interest in collaborating with the industrial partners;
  • Fluent in spoken and written English.

Conditions of employment

  • A meaningful job in a dynamic and ambitious university with the possibility to present your work at international conferences.
  • A full-time employment for temporary appointment for 1 year (with a potential of extension / promotion)
  • Close collaboration with an industrial partner (Philips) 
  • You will have free access to high-quality training programs on general skills, didactics and topics related to research and valorization.
  • A gross monthly salary and benefits in accordance with the Collective Labor Agreement for Dutch Universities.
  • A broad package of fringe benefits (including an excellent technical infrastructure, moving expenses, and savings schemes).
  • Foreign applicants may benefit from the 30% tax regulation in order to get a higher net salary, when granted.
  • Family-friendly initiatives are in place, such as an international spouse program, and excellent on-campus children day care and sports facilities.

Information and application

More information

Do you recognize yourself in this profile and would you like to know more? Please contact
prof. dr. Milan Petkovic, m.petkovic[at]tue.nl 

For information about terms of employment, please contact HRServices.MCS[at]tue.nl

Please visit www.tue.nl/jobs to find out more about working at TU/e!

Application

We invite you to submit a complete application by using the 'apply now'-button on this page.
The application should include a:

  • Cover letter in which you describe your motivation and qualifications for the position.
  • Curriculum vitae, including a list of your publications and the contact information of
    three references.
  • List of five self-selected ‘best publications’ and software artifacts developed.
  • Proof of English language skills (if applicable)

We look forward to your application and will screen it as soon as we have received it.
Screening will continue until the position has been filled.

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