Student assistant: Machine learning and FEM simulation for Sheet Metal Forming

Haustechnik Fraunhofer; Aachen; Sur place; EUR 17 000 - 25 000; Plein temps

Avantages offerts par ce poste

Flexible working hours

Thesis topics offered

Strong industry/research network

Résumé du poste

Fraunhofer IPT in Aachen is seeking a student researcher assistant to help with automation methods, ML models, and data-driven FEM simulations for sheet metal forming. Regular on-site presence in Aachen is required, with weekly hours between 10 and 17.

You will gain hands-on experience in CAE modelling (ABAQUS, Ansys), ML model development (Python, PyTorch, TensorFlow), and optimization for manufacturing process design, including possible thesis topics and documentation of results.

Qualifications

• Student in Computational Mechanics, Simulation Sciences, Mechanical Engineering or similar.
• Initial experience in CAE modelling and FEM simulation (ABAQUS/Ansys) preferred.
• Basic programming skills (Python) required.

Responsabilités

• Support automation methodology development and ML model creation.
• Develop data-driven FEM models for sheet metal forming processes.
• Assist in optimization and parameter identification for manufacturing design.
• Validate FEM/ML models with experiments and document results.

Connaissances

CAE modelling

FEM simulation

Python

PyTorch

TensorFlow

Abaqus

Ansys

Fortran

SolidWorks

Catia

English/German

Formation

Computational Mechanics

Simulation Sciences

Mechanical Engineering

Outils

ABAQUS

Ansys

PyTorch

TensorFlow

SolidWorks

Catia

Fortran

Description du poste

At the Fraunhofer IPT in Aachen, we work with more than 500 employees every day to make the production of the future more digital, more flexible and more sustainable. In the group Integrated Production Machinery, we specialize in optimizing manufacturing technologies for components used in energy conversion systems such as fuel cells and electrolyzers. With a focus on industrial applications, our expertise is concentrated on the fields of metallic bipolar plates for those applications.

As a student research assistant, you will support our team in developing automation methodology, machine learning models and data driven FEM simulation models for sheet metal forming processes. The position requires regular on-site presence at our institute in Aachen. The weekly working hours are at least 10 and at most 17 hours.

Be part of change

• CAE modelling and numerical simulation (e.g. sheet metal forming processes using ABAQUS, etc)
• Develop data-driven and machine learning-based models to improve the simulation and optimization of sheet metal forming processes
• Develop optimization methodologies for manufacturing process design and parameter identification
• Validation of the FEM and ML models through experimentation and documentation of results

What you contribute

• You are studying Computational Mechanics, Simulation Sciences, Mechanical Engineering or a comparable subject
• Initial experience in CAE modelling and FEM simulation (preferably Abaqus or Ansys) is required
• Prior knowledge of machine learning and experience in programming skills (preferably Python) is required
• Knowledge of Physics Informed Neural Networks (PINNs), PyTorch, TensorFlow is advantageous
• Experience with Fortran subroutines, automation scripting for FE software and CAD design (Solidworks, Catia) is advantageous
• Good language skills in English and/or German

What we offer

• Collaboration in innovative research projects and the ideal conditions to implement your knowledge from your studies and gain practical experience
• Flexible working to combine studies and job in the best possible way
• Opportunity to grow personally and benefit from our strong network in industry and research
• Would you like to deepen your knowledge further? We offer exciting topics for your thesis

We value and promote the diversity of our employees' skills and therefore welcome all applications - regardless of age, gender, nationality, ethnic and social origin, religion, ideology, disability, sexual orientation and identity. Severely disabled persons are given preference in the event of equal suitability. Our tasks are diverse and adaptable - for applicants with disabilities, we work together to find solutions that best promote their abilities. Remuneration according to the general works agreement for employing assistant staff.

With its focus on developing key technologies that are vital for the future and enabling the commercial utilization of this work by business and industry, Fraunhofer plays a central role in the innovation process. As a pioneer and catalyst for groundbreaking developments and scientific excellence, Fraunhofer helps shape society now and in the future.

For any further information on this position please contact:

Yogesh Borole M.Sc.

Research Assistant Integrated Production Machinery

[phone]

Fraunhofer Institute for Production Technology IPT

www.ipt.fraunhofer.de

Requisition Number: 85334 Application Deadline: