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ETH Zürich

Postdoctoral Researcher in AI-driven Surrogate Modeling for Manufacturing Process Optimization

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About the employer

ETH Zürich is well known for its excellent education, ground-breaking fundamental research and for implementing its results directly into practice.

Visit the employer page

Postdoctoral Researcher in AI-driven Surrogate Modeling for Manufacturing Process Optimization

Are you passionate about applying artificial intelligence to revolutionize traditional manufacturing processes? We are looking for a talented and motivated postdoctoral researcher to join our multidisciplinary team, working at the intersection of AI and mechanical engineering. In this exciting role, you will contribute to the development of innovative AI-based surrogate models that significantly accelerate forging process simulations, optimize manufacturing parameters, and reduce dependency on computationally expensive simulations.

This position offers the opportunity to work with leading experts, access state-of-the-art computational resources, and contribute to high-impact research that bridges academia and industry. If you have a strong background in AI, machine learning, and a keen interest in real-world applications, we encourage you to apply and be part of this exciting journey.

Project background

Manufacturing process optimization is a critical challenge in the modern industrial landscape, particularly in high-precision industries such as aerospace, automotive, and energy. Current methodologies in processes like forging rely heavily on computationally expensive simulations based on Smoothed Particle Hydrodynamics (SPH) or Finite Element Method (FEM), which require significant computational resources and expert knowledge. These traditional methods lead to prolonged development cycles and increased costs. The demand for rapid and accurate process optimization solutions is increasing, driven by the need to reduce time-to-market and production costs while maintaining high-quality standards.

This project aims to develop a novel AI-driven solution to revolutionize forging process optimization by leveraging surrogate modeling techniques. The objective is to create an AI-based tool that can:

  • Accurately simulate forging processes in milliseconds instead of hours
  • Predict optimal process parameters with high accuracy
  • Reduce dependency on expensive simulations based SPH or FEM
  • Enable real-time decision-making in production environments

Job description

  • Design and implement data augmentation techniques to enhance model performance
  • Implement efficient parametrization methods for geometries and workpiece properties such as temperature or strain
  • Develop and optimize AI-based surrogate models for manufacturing processes
  • Develop a user-friendly graphical interface (GUI) for interaction with the AI model, including real-time analytics and visualization
  • Prepare manuscripts, reports, and presentations to disseminate findings
  • Maintain thorough documentation of model development and project progress

Profile

Required

  • PhD in Computer Science with the focus on AI
  • Proficiency in python programming 
  • Strong expertise in machine learning and deep learning frameworks (especially PyTorch)
  • Demonstrated ability to work independently and as part of a multidisciplinary team
  • Excellent written and verbal communication skills (Proficiency in English; German is a plus)

Preferred

  • Basic familiarity with FEM and SPH
  • Knowledge of manufacturing processes, especially forging
  • Experience with computer graphics concepts such as implicit modeling, mesh processing, or CAD-related tasks
  • Familiarity with reinforcement learning

We offer

The open position is in the Advanced Manufacturing Laboratory (Prof. Dr. Markus Bambach) within the Department of Mechanical and Process Engineering (D-MAVT) at ETH Zurich in Zurich, Switzerland.

We offer a 2-year project-based contract starting in Spring/Summer 2025 that includes:

  • Opportunities to engage with different communities bridging machine learning and mechanical engineering leading to high impact publications
  • You will be part of a highly motivated, multidisciplinary and collaborative team
  • We will support your scientific career and application for postdoctoral fellowships on your path towards scientific leadership
  • Access to state-of-the-art computational resources and collaborative research networks
  • Opportunities for professional development and career advancement
Working, teaching and research at ETH Zurich

We value diversity

In line with our values, ETH Zurich encourages an inclusive culture. We promote equality of opportunity, value diversity and nurture a working and learning environment in which the rights and dignity of all our staff and students are respected. Visit our Equal Opportunities and Diversity website to find out how we ensure a fair and open environment that allows everyone to grow and flourish.

Curious? So are we.

We look forward to receiving your online application with the following documents:

  • a letter of motivation (1-page max)
  • CV 
  • PhD diploma

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 the website. Questions regarding the position should be directed to Dr. Jan Petrik, by email at jan.petrik@ethz.ch (no applications).

About ETH Zürich

ETH Zurich is one of the world’s leading universities specialising in science and technology. We are renowned for our excellent education, cutting-edge fundamental research and direct transfer of new knowledge into society. Over 30,000 people from more than 120 countries find our university to be a place that promotes independent thinking and an environment that inspires excellence. Located in the heart of Europe, yet forging connections all over the world, we work together to develop solutions for the global challenges of today and tomorrow.

Job details

Title
Postdoctoral Researcher in AI-driven Surrogate Modeling for Manufacturing Process Optimization
Employer
Location
Rämistrasse 101 Zurich, Switzerland
Published
2025-01-21
Application deadline
Unspecified
Job type
Save job

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About the employer

ETH Zürich is well known for its excellent education, ground-breaking fundamental research and for implementing its results directly into practice.

Visit the employer page

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