PhD position in Predictive Asset Maintenance using Operations Research and Machine Learning (1.0 FTE)
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PhD position in Predictive Asset Maintenance using Operations Research and Machine Learning (1.0 FTE) |
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Job description |
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Modern vehicles are equipped with sensors that continuously monitor the health of components. The availability of sensor measurements opens up the opportunity to analyse degradation trends over time, and to plan maintenance accordingly. We aim to develop predictive maintenance models for fleets of vehicles whose health is continuously monitored by sensors. |
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Qualifications |
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We are looking for an enthusiastic new colleague who meets the following criteria:
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Offer |
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In addition to the employment conditions from the CAO for Dutch Universities, Utrecht University has a number of its own arrangements. These include agreements on professional development, leave arrangements and sports. We also give you the opportunity to expand your terms of employment through the Employment Conditions Selection Model. This is how we encourage you to grow. |
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About the organization |
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A better future for everyone. This ambition motivates our scientists in executing their leading research and inspiring teaching. At Utrecht University , the various disciplines collaborate intensively towards major societal themes. Our focus is on Dynamics of Youth, Institutions for Open Societies, Life Sciences and Sustainability. |
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Additional information |
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If you have any questions that you’d like us to answer, please contact Dr Mihaela Mitici at [email protected] . |
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Apply |
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We aim to embed good equality and diversity practices in all our activities so that we can provide an inclusive, welcoming and inspiring place to work and study regardless of age, disability, trans identity or history, marital status, pregnancy and maternity, race, religion, gender or sexual orientation.
If you are within a few months from the completion of your MSc degree, we also welcome you to apply! In that case, please enclose a letter from your MSc thesis supervisor indicating when you are likely to graduate. |
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The application deadline is |
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07/01/2023 |
Forward vacancy
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