Student Project Assistant (m/f/x) at the Christian Doppler Laboratory for Physics-Based Machine Learning in Industrial Applications

Jobbeschreibung

Responsibilities

• Writing code (Python) in the fields of numerical simulation and machine learning
• Validating methods
• Implementing coding tests
• Creating graphics
• Presenting results

Admission Requirements

• Bachelor of Science (BSc) degree in Mechanical Engineering, Process Engineering, Engineering Physics, Computer Science, or a comparable field of study

Desired Qualification

• Interest in numerical simulation and machine learning
• Programming skills in Python
• Ability to work independently and in a structured manner
• Very good knowledge of German or English

We Offer

• Interesting area of responsibility

• Collegial and friendly working atmosphere

• Flexible working schedule

• International training and teaching opportunities

• Gain work experience relevant to your studies

• Family-friendly employer

• Subsidy for public transport

• University's sports program

• Shopping Discounts

• Workplace Health Management

• Top infrastructure and access to the latest technologies

• Exciting opportunities for professional and personal development

Graz University of Technology aims to increase the proportion of women, in particular in management and academic staff, and therefore qualified female applicants are explicitly encouraged to apply. Preference will be given to women if applicants are equally qualified.

Graz University of Technology actively promotes diversity and equal opportunities. Applicants are not to be discriminated against in personnel selection procedures on the grounds of gender, ethnicity, religion or ideology, age, sexual orientation (Anti-discrimination).

People with disabilities and who have the relevant qualifications are expressly invited to apply.

About us

Graz University of Technology is the longest-established university of technology in Austria. Here, successful teams of students, talented up-and-coming scientists, ambitious researchers and a lively start-up scene enjoy an inspirational environment as well as access to top-quality equipment. And all this in one of the most innovative and livable regions in Europe. TU Graz offers an inspiring working environment with outstanding infrastructure and service-oriented university management.

In this video, we give you an insight into the working environment at TU Graz: HERE

Organisational Unit

The CD Laboratory for Physics-Based Machine Learning in Industrial Applications is based at the Institute for Thermodynamics and Sustainable Propulsion Systems and aims to improve the applicability of machine learning (ML) to engineering problems. Specific examples include numerical simulations in the fields of structural mechanics and fluid dynamics, as well as predictive simulation and control. Although recent research activities have demonstrated the enormous potential of physics-based ML, significant research effort is required to develop stable and generally applicable methods. The CD Lab's holistic research approach focuses on the possibilities of integrating physics-based information throughout the entire ML process, including problem formulation, data generation and preparation, ML architecture, and the training process. Through comprehensive basic research, novel ML approaches are being explored that incorporate not only physical information but also elements of numerical simulation to improve the training process. These research activities will significantly expand the extrapolation capabilities of ML models to enable reliable predictions in scenarios or under conditions that are underrepresented or absent in the underlying training data.

Contact

Institute for Thermodynamics and Sustainable Propulsion Systems

Ass. Prof. Dr. Stefan Posch

Extra Informationen

Status

Offen

Ausbildungsniveau

Andere

Standort

Graz

Jobart

Vollzeitstelle

Veröffentlicht am

06-11-2026

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