Postdoc Explainable AI for sequential data from industrial systems
Eindhoven University of Technology, the Netherlands is looking for a Postdoc for a project on Explainable AI for sequential data from industrial systems
Optimization of manufacturing processes is turning to data-driven approaches, aiming to leverage the available data. A major obstacle in adopting many of these data-driven methods in the manufacturing industry is their black-box nature.
Deep neural network models of high dimensional data can reach very high performance ,n a supervised learning setting. However, their applicability is still challenged by a number of drawbacks: their behavior is hard to interpret, it is hard to provide strong guarantees of generalization, it is hard to incorporate existing domain knowledge in their training process, and it is hard to apply in real contexts where data is noisy, corrupted or violating the i.i.d. assumption.
We are looking /or candidates that would like to tackle these challenges and are interested in working on any of the following topics:
- Disentanglement of latent factors /or high dimensional data, particularly sequential and time series;
- Generative models for the simulation of complex systems;
- Deep Metric learning for capturing expert knowledge
This position is funded by the MADEin4 European project targeting the design and validation of data driven methods and tools /or metrology in semiconductor industry. The project is joined by around 40 industrial and academic partners. Our focus is on developing explainable modelling methods /or sequential data incorporating expert knowledge in the optimization processes that will benefit /rom the expert knowledge and help build confidence in the model predictions, to ease the adoption of data driven approaches in the industry.
The successful candidates are expected to:
- perform scientific research in the domain described above;
- publish results at (international) conferences;
- collaborate with other group and faculty members;
- collaborate with selected MADEin4 project partners, attend project meetings and contribute to deliverables and project outcome;
- assist with educational tasks (e.g. supervise Master students and internships)
- You have a strong background in machine learning, statistics or stochastics.
- You have a PhD in Computer Science, (Applied) Mathematics, Information Technologies, or a related field.
- You have good programming skilIs and experience (Python is an asset).
- You have good communicative skilIs and are eager to work as part of a research team.
- You are creative and ambitious.
- You have good command of the English language (knowledge of Dutch is not required).
CONDITIONS OF EMPLOYMENT
- We offer a one-year contract (full-time employment) that can be extended for two years after a positive evaluation.
- Gross monthly salary from € 2.790 to € 4.402 (depending on work experience) in accordance with the Collective Labor Agreement for Dutch Universities.
- A yearly holiday allowance of 8% as well as 8.3% end of the year allowance.
- A broad and attractive package of fringe benefits (including an excellent technical infrastructure, moving expenses, and savings schemes).
- You will have free access to high-quality training programs for research and valorization, professional development courses for PhD students, and didactical courses of the TEACH training program.
- Family-friendly initiatives are in place, such as an international spouse program, and excellent on-campus children day care and sports facilities.
Do you recognize yourself in this profile and would you like to know more? Please contact Mr. M. Holenderski m.holenderski[at]tue.nl or +31 40 247 5203.
For information about terms of employment, please contact Mrs. K. Wels-Noordermeer, HR Advisor k.h.wels[at]tue.nl or +31 40 247 4329.
Please visit www.tue.nl/jobs to find out more about working at TU/e!
We invite you to submit a complete application by using the 'apply now'-button on this page.
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.
- List of five self-selected 'best publications'.
You can upload max. five files with all the required documents (max. 5 MB).
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