Project Engineer: Data-Driven Optimization of Manufacturing Processes
80%-100%, Zurich, fixed-term
The chair of Artificial Intelligence in Mechanics and Manufacturing at ETH Zurich, led by Prof. Dr. Dirk Mohr, combines physically motivated models with advanced ML approaches to solve challenges in constitutive and process modeling. We bridge the gap between theoretical research and industrial applications through close collaborations with industry partners, applying cutting-edge scientific discoveries to real-world manufacturing problems.
Project background
Numerical simulations are essential for designing and assessing the quality of casting products. However, their high computational cost presents a challenge for real-time process control. This project aims to overcome this limitation by integrating real-world casting data, process parameters, and finite element method (FEM) simulations using metamodeling techniques and Machine Learning (ML). By enriching datasets and leveraging advanced simulations to optimize ML models, we seek to enhance manufacturing efficiency and quality control in casting processes.
Job description
We are looking for a highly motivated researcher to join our team and contribute to projects at the intersection of computational modeling, data science, and industrial applications. As part of this position, you will:
- Develop and implement advanced Machine Learning models to analyze large datasets, including image and time-series data.
- Investigate and quantify the relationships between manufacturing process parameters, failure mechanisms, and product quality.
- Optimize manufacturing processes to enhance product reliability and quality.
- Collaborate closely with industrial partners to translate research findings into practical applications.
Profile
We are seeking a candidate with the following qualifications:
- A Master’s degree in engineering, physics, computational sciences, or a related field.
- A strong interest in computational modeling and data-driven optimization.
- Proficiency in Python programming.
- A proactive, solution-oriented mindset with a willingness to engage in interdisciplinary research.
- Excellent communication skills and the ability to work effectively in a collaborative team environment.
Workplace
Workplace
We offer
This position provides a unique opportunity to work at the intersection of research and industry, applying data-driven techniques to shape the future of manufacturing. You will:
- Conduct cutting-edge research in a dynamic and innovative team.
- Gain exposure to the Swiss manufacturing sector through collaborations with leading industrial partners.
- Contribute to real-world advancements in computational engineering and process optimization.
Join us and make a tangible impact on next-generation manufacturing technologies!
We value diversity
Curious? So are we.
We look forward to receiving your online application with the following documents:
- cover letter
- CV
- transscirpts of all degress
Please note that we exclusively accept applications submitted through our online application portal. Applications via email or postal services will not be considered.
Further information about our lab can be found on our website. Questions regarding the position should be directed to Martina Koch martikoc@ethz.ch .
For recruitment services the GTC of ETH Zurich apply.
About ETH Zürich
Curious? So are we.
We look forward to receiving your online application with the following documents:
- cover letter
- CV
- transscirpts of all degress
Please note that we exclusively accept applications submitted through our online application portal. Applications via email or postal services will not be considered.
Further information about our lab can be found on our website. Questions regarding the position should be directed to Martina Koch martikoc@ethz.ch .
For recruitment services the GTC of ETH Zurich apply.