Postdoc Position on Reduced Order Models: The MAST-group at the University of Twente is inviting applications for a postdoctoral researcher for an 18-month period. This position is part of a collaborative effort to reduce CO2 emissions in steel production using machine learning technologies.
Postdoc Position on Data-Enhanced Physical Reduced Order Models
Designation: Postdoctoral Researcher
Research Area:
Data-Enhanced Physical Reduced Order Models in the context of machine learning applications for CO2 reduction in industrial processes.
Location:
University of Twente, Enschede, Netherlands
Eligibility/Qualifications:
- Must hold a PhD in Mathematics or a related field.
- Knowledge of model reduction, physics, and/or chemistry is advantageous.
- Strong analytical, communication, and creative problem-solving skills.
- Ability to work collaboratively in an interdisciplinary and international environment.
- Fluent in English.
Job Description:
The successful candidate will engage in theoretical and applied projects focusing on data-enhanced physical reduced order models and will serve as a data science expert within an interdisciplinary consortium. Responsibilities include:
- Conducting research to enhance physical models with data-driven approaches.
- Collaborating closely with academic and industrial partners on targeted projects.
- Contributing to software development and data integration efforts.
How to Apply:
Interested candidates should submit their applications through the online portal by including a CV, motivation letter, and a list of publications. For questions, please contact Dr. Silke Glas at s.m.glas@utwente.nl.
Last Date for Apply:
September 10, 2025
For further details, applicants are encouraged to refer to the University of Twente’s official website or reach out directly via the provided contact information.
