Postdoc: Statistical Modelling and Analysis of Reliability Data for LED Lighting
Postdoc: Statistical Modelling and Analysis of Reliability Data for LED Lighting
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This postdoc position offers a unique opportunity to work in the interface of academic and industrial
research.
Job description
The postdoctoral researcher will work in the context of the Al-Twilight project (Al-digital TW/n for l/GHTing), that will be carried about by a European consortium involving several universities and industrial partners.
Although the main goals are the development of methodology, the postdoctoral researcher will work in close collaboration with companies such as Signify (formerly Philips lighting). There will be ample opportunity to implement and test novel methodologies in a cutting-edge industrial research environment. This postdoc position offers a unique opportunity to work in the interface of academic and industrial research.
The goal of the Al-Twilight project is to develop a digital twin based on multidomain physical models of packaged LED chips. An importance purpose of this digital twin is to provide predictions for remaining product lifetime. The postdoc will develop in this digital twin context new statistical methods for data-driven lifetime predictions for LED lighting as well as new efficient sequential statistical testing protocols. Statistical challenges involve dealing with limited failure data, extrapolation and minimizing test time by allowing early decisions.
The postdoc will work within the statistics group at TU/e, which is located within in the Department of Mathematics and Computer Science. Apart from the statistics group at TU/e, two other groups at TU/e participate in Al-Twilight with a PhD student or postdoc: the Scientific Computing group (same department) and the Human-Technology Interaction (HTI) group within the Department of Industrial Engineering and Innovation Sciences. The Intelligent lighting Institute {Ill}, TU/e's interdepartmental institute for innovations in lighting, is also involved in this project.
The statistics group at TU/e focusses both on theoretical and applied research. The research areas cover a wide range of topics: hypothesis testing (equivalence, non-inferiority), statistical process monitoring, survival and reliability theory, causality, mixed and latent variable models, nonparametric statistics, high-dimensional statistics, and statistical learning theory. The group actively explores new research lines in Data Science and has strong ties with industrial partners in various business domains, particularly the high-tech industry in the Brainport region around Eindhoven.
The statistics group is part of the SPOR (Statistics, Probability Theory and Operations Research} cluster within the TU/e subdepartment Mathematics. The SPOR cluster currently has 4 full professors, 6 part-time professors, 3 associate professors and 14 assistant professors. In addition, the cluster is strongly intertwined with EURANDOM, the European institute for research in Statistics, Probability and Stochastic Operations Research. EURANDOM is a workshop and visitor center that exists since 1998.
The Mathematics and Computer Science department consists of three charters: Mathematics, Computer Science, and Data Science. Knowledge valorisation within the department takes place through the Project Development Office (PDO). The department actively participates in EA/SI, the Eindhoven Artificial Intelligence Systems Institute, a research institute covering many facets of data science and artificial intelligence. In the education and research areas, the department works closely together with other universities and with companies. TU/e is located in Brainport, an internationally renowned high-tech industrial area around Eindhoven with companies like Signify (formerly Philips Lighting), ASML and NXP. Brainport also hosts the High Tech Campus, where 5000 industrial researchers from companies work together. This stimulating industrial environment enables TU/e to maintain close links with industry, healthcare and the building and logistics sectors.
Although the main goals are the development of methodology, the postdoctoral researcher will work in close collaboration with companies such as Signify (formerly Philips lighting). There will be ample opportunity to implement and test novel methodologies in a cutting-edge industrial research environment. This postdoc position offers a unique opportunity to work in the interface of academic and industrial research.
The goal of the Al-Twilight project is to develop a digital twin based on multidomain physical models of packaged LED chips. An importance purpose of this digital twin is to provide predictions for remaining product lifetime. The postdoc will develop in this digital twin context new statistical methods for data-driven lifetime predictions for LED lighting as well as new efficient sequential statistical testing protocols. Statistical challenges involve dealing with limited failure data, extrapolation and minimizing test time by allowing early decisions.
The postdoc will work within the statistics group at TU/e, which is located within in the Department of Mathematics and Computer Science. Apart from the statistics group at TU/e, two other groups at TU/e participate in Al-Twilight with a PhD student or postdoc: the Scientific Computing group (same department) and the Human-Technology Interaction (HTI) group within the Department of Industrial Engineering and Innovation Sciences. The Intelligent lighting Institute {Ill}, TU/e's interdepartmental institute for innovations in lighting, is also involved in this project.
The statistics group at TU/e focusses both on theoretical and applied research. The research areas cover a wide range of topics: hypothesis testing (equivalence, non-inferiority), statistical process monitoring, survival and reliability theory, causality, mixed and latent variable models, nonparametric statistics, high-dimensional statistics, and statistical learning theory. The group actively explores new research lines in Data Science and has strong ties with industrial partners in various business domains, particularly the high-tech industry in the Brainport region around Eindhoven.
The statistics group is part of the SPOR (Statistics, Probability Theory and Operations Research} cluster within the TU/e subdepartment Mathematics. The SPOR cluster currently has 4 full professors, 6 part-time professors, 3 associate professors and 14 assistant professors. In addition, the cluster is strongly intertwined with EURANDOM, the European institute for research in Statistics, Probability and Stochastic Operations Research. EURANDOM is a workshop and visitor center that exists since 1998.
The Mathematics and Computer Science department consists of three charters: Mathematics, Computer Science, and Data Science. Knowledge valorisation within the department takes place through the Project Development Office (PDO). The department actively participates in EA/SI, the Eindhoven Artificial Intelligence Systems Institute, a research institute covering many facets of data science and artificial intelligence. In the education and research areas, the department works closely together with other universities and with companies. TU/e is located in Brainport, an internationally renowned high-tech industrial area around Eindhoven with companies like Signify (formerly Philips Lighting), ASML and NXP. Brainport also hosts the High Tech Campus, where 5000 industrial researchers from companies work together. This stimulating industrial environment enables TU/e to maintain close links with industry, healthcare and the building and logistics sectors.
Specifications
- max. 30.4 hours per week
- Eindhoven View on Google Maps
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Eindhoven University of Technology (TU/e)
Requirements
Applicants are required to have a PhD degree in mathematics, statistics or computer science.
In view of the close collaboration with industrial partners, candidates should have interest in applied statistical research in an industrial context and have the proficiency necessary to implement and test novel computational methodologies.
In view of the close collaboration with industrial partners, candidates should have interest in applied statistical research in an industrial context and have the proficiency necessary to implement and test novel computational methodologies.
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 station. In addition, we offer you:
A Staff Immigration Team is available for international candidates, as are a tax compensation scheme (the 30% facility) and a compensation for moving expenses.
- Full-time employment for 18 months.
- Salary in accordance with the Collective Labour Agreement for Dutch Universities,
scale 10. - A year-end bonus of 8.3% and annual vacation pay of 8%.
- High-quality training programs on general skills, didactics and topics related to research and valorization.
- An excellent technical infrastructure, on-campus children's day care and sports facilities.
- Partially paid parental leave and an allowance for commuting, working from home and internet costs.
- A TU/e Postdoc Association that helps you to build a stronger and broader academic and personal network, and offers tailored support, training and workshops.
A Staff Immigration Team is available for international candidates, as are a tax compensation scheme (the 30% facility) and a compensation for moving expenses.
