Are you interested in developing models describing the degradation and failure of components, and at the same time working with real data and military systems from e.g. the Royal Netherlands Navy ? And are you interested in collaborating with a range of industrial partners and several universities and research institutes to develop methods and algorithms to achieve Predictive Maintenance? The joint research program of the Netherlands Defence Academy (NLDA) and the Dynamics based Maintenance group, Faculty of Engineering Technology at the University of Twente, The Netherlands has several openings for doctoral (PhD) candidates within the research area of Modeling Degradation and Failures for Predictive Maintenance.
To increase the availability and reliability of critical systems, while at the same time reducing maintenance costs, data from sensors and inspections is used more and more to better detect or even predict failures. Instead of depending fully on data, our vision is that knowledge of the underlying physical (degradation) mechanisms strongly improves the predictions. The aim of the current research program is therefore to develop novel methods and models describing the degradation and failure of critical components. These models will then be used to improve the (automatic) detection, diagnosis and prediction of failures, and to model the system reliability. Developed methods are applied in the military field (ships, vehicles, helicopters), as well as in industries in the maritime (ship, wind turbines), energy, process and manufacturing sectors. Typical systems for which degradation models should be developed are sustainable propulsion systems like fuel cells and internal combustion engines fueled by ammonia, standard equipment types like pumps and chillers, electronic systems like radars, but also corrosion protection coatings on maritime structures. Collaboration in both national and European projects with the ministry of defence, its industrial partners and several universities and research institutes allows the researchers to work with real data from both civil and military advanced systems.Your profile
The successful applicant has a master's degree and background in material science, applied physics, mechanical / aerospace / maritime engineering, or similar areas. As the projects are multidisciplinary, candidates are expected to be open for / have affinity with especially data science, but also with other domains than their own background. Good spoken and written English and the ability to work in a team are mandatory. As the work is defence-related, a security screening will be part of the selection process, and candidates are preferably from a NATO country.Our offer
The work in these projects will mainly take place at the Knowledge Centre Smart Maintenance of the Netherlands Defence Academy (NLDA), located in Den Helder, but can be combined with working at the Dynamics based Maintenance group at the University of Twente. The NLDA offers an innovative and inspiring working environment, with direct access to a range of highly technological systems. The UT provides a dynamic and international environment, combining the benefits of academic research with a topic of high industrial relevance, excellent working conditions, an exciting scientific environment, and a green and lively campus.
You can apply for this position before January 15, 2023 by clicking the ‘apply now' button below . Please include:
For more information on this position, please contact Prof. Tiedo Tinga, firstname.lastname@example.org.
A game-based assessment will be part of the selection process.
The first job interviews are planned on Tuesday 31 January, 2023.About the organization
The Faculty of Engineering Technology (ET) engages in education and research of Mechanical Engineering, Civil Engineering and Industrial Design Engineering. We enable society and industry to innovate and create value using efficient, solid and sustainable technology. We are part of a ‘people-first' university of technology, taking our place as an internationally leading center for smart production, processes and devices in five domains: Health Technology, Maintenance, Smart Regions, Smart Industry and Sustainable Resources. Our faculty is home to about 2,900 Bachelor's and Master's students, 550 employees and 150 PhD candidates. Our educational and research programmes are closely connected with UT research institutes Mesa+ Institute, TechMed Center and Digital Society Institute.How to apply Step 1
Apply. When you see a vacancy that appeals to you, you can apply online. We ask you to upload a CV and motivation letter and/or list of publications. You will receive a confirmation of receipt by e-mail.Step 2
Selection. The selection committee will review your application and you will receive a response within 2 weeks after the vacancy has been closed.Step 3
1st interview. The 1st (online or in person) meeting serves as an introduction where we introduce ourselves to you and you to us. You may be asked to give a short presentation. This will be further explained in the invitation.Step 4
2nd interview. In the second interview, we will further discuss the job content, your skills and your talents.Step 5
The offer. If the conversations are positive, you will be made a suitable offer.Want to know more Tinga, T. (Tiedo)
Full Professor Dynamics based MaintenanceTinga, T. (Tiedo)
Full Professor Dynamics based Maintenance
Do you have questions about this vacancy? Then you can contact Tiedo for all substantive questions about this position and the application procedure. For general questions about working for the UT, please refer to the chatbot.Contact
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