PhD on AI-driven Repair Recommendations for Sustainable Manufacturing
PhD on AI-driven Repair Recommendations for Sustainable Manufacturing
Employer Active
Job Alert
You will be updated with latest job alerts via email
Share
Job Alert
You will be updated with latest job alerts via email
Not Disclosed
Salary Not Disclosed
1 Vacancy
Job Description
Departments Department of Industrial Engineering & Innovation Sciences
Eindhoven University of Technology is an internationally top-ranking university in the Netherlands that combines scientific curiosity with a hands-on attitude. Our spirit of collaboration translates into an open culture and a top-five position in collaborating with advanced industries. Fundamental knowledge enables us to design solutions for the highly complex problems of today and tomorrow.
The Industrial Engineering & Innovation Sciences (IE&IS) department combines disciplinary knowledge from the humanities social sciences and technical sciences to solve the complex problems of industries and society. We collaboratively focus on and create responsible and effective innovations for the research themes: Humans and Technology Supply Chain Management Sustainability and Circularity and Value of Data-Driven Intelligence.
Introduction
Are you passionate about developing intelligent algorithms that can support repair and remanufacturing decisions for sustainable manufacturing As a PhD researcher you will create innovative machine learning solutions to optimize the component lifecycle directly contributing to a more circular economy.
Job Description
In the manufacturing landscape determining whether a component should be repaired reused or discarded requires sophisticated condition assessment and decision-making capabilities. This PhD project tackles a critical challenge: how to develop robust machine learning models that can accurately predict component health and optimize repair decisions.
You will develop novel data-centric approaches to Remaining Useful Life (RUL) prediction that goes beyond traditional model-focused methods. You will focus on understanding and improving how data is collected managed and utilized throughout the entire process. Your research will encompass developing machine learning techniques that thrive with imperfect data creating adaptive models that can quickly learn from new machines with minimal training data and integrating these predictions with optimization algorithms to make cost-effective and environmentally sustainable decisions about component lifecycle management.
You will be part of the large ADD-reAM project an NWO-funded consortium having 15 PhD researchers exploring complementary aspects of additive manufacturing including technical design logistics sustainability assessment and regulatory frameworks. Your PhD position will be embedded in the Information Systems group within the Department of Industrial Engineering and Innovation Sciences (IE&IS) at Eindhoven University of Technology (TU/e) collaborating closely with researchers working on predictive maintenance operational decision-making and artificial intelligence.
Job Requirements
- A masters degree (or an equivalent university degree) in Computer Science Machine Learning Operations Research or a related technical field.
- Strong background in deep learning with a motivation to advance fundamental techniques.
- Excellent analytical problem-solving and software engineering skills with prior experience implementing machine learning algorithms using well-known frameworks (e.g. PyTorch).
- Ability to work in an interdisciplinary team and interested in collaborating with industrial partners.
- Motivated to develop teaching skills and coaching skills.
- Strong communication skills including proficiency in written and spoken English (C1).
Conditions of Employment
A meaningful job in a dynamic and ambitious university in an interdisciplinary setting and within an international network. You will work on a beautiful green campus within walking distance of the central train addition we offer you:
- Full-time employment for four years with an intermediate assessment after nine months. You will spend a minimum of 10% of your four-year employment on teaching tasks with a maximum of 15% per year of your employment.
- Salary and benefits (such as a pension scheme paid pregnancy and maternity leave partially paid parental leave) in accordance with the Collective Labour Agreement for Dutch Universities scale P (min. 3059 max. 3881).
- A year-end bonus of 8.3% and annual vacation pay of 8%.
- High-quality training programs and other support to grow into a self-aware autonomous scientific researcher. At TU/e we challenge you to take charge of your own learning process.
- An excellent technical infrastructure on-campus childrens day care and sports facilities.
- An allowance for commuting working from home and internet costs.
- A Staff Immigration Team and a tax compensation scheme (the 30% facility) for international candidates.
Information
Do you recognize yourself in this profile and would you like to know more Please . Remco Dijkman () or . Zaharah Bukhsh ().
Visit our website for more information about the application process or the conditions of employment. You can also contact .
Are you inspired and would like to know more about working at TU/e Please visit our career page.
Application
We invite you to submit a complete application by using the apply button. 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.
- Copies of diplomas and academic transcripts with grades from prior university studies.
- MSc thesis (in English) and/or research work.
We look forward to receiving your application and will screen it as soon as possible. The vacancy will remain open until the position is filled.
Return to job vacancies
Employment Type
Full-Time
