Phd Position Predictive Aircraft Maintenance
2 maanden geleden
PhD Position Predictive Aircraft Maintenance-
**_Challenge: Predict the minimum failure time of aircraft components_**
**_ Change: Use both classical data science methods and machine learning_**
**_ Impact: Safe and more efficient aircraft maintenance_**
Job description
Imagine you are going on holidays: You take the train to the airport and enjoy a coffee while the aircraft takes off. Though we often don’t think about it, the train, the aircraft and even the coffee machine on the aircraft would not work without maintenance.
In this PhD, you will research a new maintenance strategy, called predictive maintenance, that makes this maintenance more efficient. In predictive maintenance, we use the measurements from sensors around components (measuring for instance the temperature) to predict the time left until the failure of the component (called the Remaining Useful Life, RUL). Your efforts will focus on aircraft predictive maintenance.
We cannot predict the RUL with absolute certainty. You will therefore predict a distribution for the RUL. The challenging, but also fun, part about aircraft maintenance, is that safety is of paramount important. We are therefore specifically interested in predicting the minimum value of the RUL by predicting and modelling the left tail of the RUL distribution. In this way, we can answer questions such as “Is the probability that the component will fail within the next week 1% or 0.1%?”. To do so, you will combine (classical) data science methods with modern machine learning, statistics and methods from the field of extreme value theory and rare event simulation.
**Requirements**:
The requirements are:
- You have completed or are about to complete a master with a quantitative background, for instance (but not limited to) aerospace engineering with a focus on optimization, econometrics, mathematics or statistics.
- You are proficient in English.
- Due to the expiration date of the funding, you are able to start (and thus have completed your master) before or on 1-1-2025.
Besides this, it is nice, but not required, if you have some knowledge about either maintenance, aviation, statistics, (classical) data science methods, machine learning, rare event simulation or the extreme value theory.
Conditions of employment
The TU Delft offers a customisable compensation package, discounts on health insurance, and a monthly work costs contribution. Flexible work schedules can be arranged.
For international applicants, TU Delft has the Coming to Delft Service. This service provides information for new international employees to help you prepare the relocation and to settle in the Netherlands. The Coming to Delft Service offers a Dual Career Programme for partners and they organise events to expand your (social) network.
TU Delft (Delft University of Technology)
Delft University of Technology is built on strong foundations. As creators of the world-famous Dutch waterworks and pioneers in biotech, TU Delft is a top international university combining science, engineering and design. It delivers world class results in education, research and innovation to address challenges in the areas of energy, climate, mobility, health and digital society. For generations, our engineers have proven to be entrepreneurial problem-solvers, both in business and in a social context.
Challenge. Change. Impact
Faculty Aerospace Engineering
Click here to go to the website of the Faculty of Aerospace Engineering.
Additional information
Due to the prompt start date of the position (to prevent that the funding expires), only EU-citizens or people with a EU work permit are eligible for this position.
Application procedure
- A pre-employment screening can be part of the selection procedure.
- Please do not contact us for unsolicited services.
- FACULTY/DEPARTMENT***
**Faculty of Aerospace Engineering**:
- JOB TYPE***
**PhD**:
- SCIENTIFIC FIELD***
**Engineering**:
- HOURS PER WEEK***
**38**:
- SALARY***
**€ 2.872,00 - € 3.670,00**:
- DESIRED LEVEL OF EDUCATION***
**University graduate**:
- VACANCY NUMBER***
**TUD05754**:
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