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Master's thesis 'Development of an ML-based framework for the design of radial compressors'(m/w/x)
Developing an ML-based framework for radial compressor design, integrating CAE and simulation tools. Python programming and turbomachinery knowledge required. Flexible hours, mobile and on-site work.
Anforderungen
- Ongoing master's studies in mechanical, energy, or process engineering
- Solid knowledge of turbomachinery/fluid machinery
- Programming experience in Python
- Independent work ability
- Interest in machine learning (ML)
Aufgaben
- Develop and integrate CAE interface solutions
- Link simulation and design tools into optimization processes
- Focus on fluid dynamics and structural mechanics simulations
- Design and develop turbomachinery and flow-through components
- Research ML-based approaches for turbo-machine components
- Develop an overall concept for an ML-based design framework
- Collect and analyze existing CFD data from previous designs
- Identify and resolve inconsistencies in CFD data
- Process data into a consistent, usable training dataset
- Develop an automated workflow for building the ML model
- Evaluate the reliability and robustness of the ML model
Ausbildung
- Laufendes Studium
Sprachen
- Englisch – verhandlungssicher
Tools & Technologien
- Python
- Machine learning (ML)
Benefits
Flexibles Arbeiten
- Flexible working hours
Sonstige Vorteile
- Mobile and on-site work
- Diversity and inclusion
- Comprehensive onboarding
- Good support
- Keynote speeches
Lockere Unternehmenskultur
- Open-minded team
- Cooperative teamwork
Weiterbildungsangebote
- Combine studies with practical experience
- Training
Karriere- und Weiterentwicklung
- Networking opportunities
- Career development support
Gesundheits- & Fitnessangebote
- Health offers
Mentale Gesundheitsförderung
- Well-being support
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Master's thesis 'Development of an ML-based framework for the design of radial compressors'(m/w/x)
Developing an ML-based framework for radial compressor design, integrating CAE and simulation tools. Python programming and turbomachinery knowledge required. Flexible hours, mobile and on-site work.
Anforderungen
- Ongoing master's studies in mechanical, energy, or process engineering
- Solid knowledge of turbomachinery/fluid machinery
- Programming experience in Python
- Independent work ability
- Interest in machine learning (ML)
Aufgaben
- Develop and integrate CAE interface solutions
- Link simulation and design tools into optimization processes
- Focus on fluid dynamics and structural mechanics simulations
- Design and develop turbomachinery and flow-through components
- Research ML-based approaches for turbo-machine components
- Develop an overall concept for an ML-based design framework
- Collect and analyze existing CFD data from previous designs
- Identify and resolve inconsistencies in CFD data
- Process data into a consistent, usable training dataset
- Develop an automated workflow for building the ML model
- Evaluate the reliability and robustness of the ML model
Ausbildung
- Laufendes Studium
Sprachen
- Englisch – verhandlungssicher
Tools & Technologien
- Python
- Machine learning (ML)
Benefits
Flexibles Arbeiten
- Flexible working hours
Sonstige Vorteile
- Mobile and on-site work
- Diversity and inclusion
- Comprehensive onboarding
- Good support
- Keynote speeches
Lockere Unternehmenskultur
- Open-minded team
- Cooperative teamwork
Weiterbildungsangebote
- Combine studies with practical experience
- Training
Karriere- und Weiterentwicklung
- Networking opportunities
- Career development support
Gesundheits- & Fitnessangebote
- Health offers
Mentale Gesundheitsförderung
- Well-being support
Gefällt dir diese Stelle?
BetaDein Career Agent findet täglich ähnliche Jobs für dich.
Über das Unternehmen
Fraunhofer Institute for Environmental, Safety, and Energy Technology UMSICHT
Branche
Research
Beschreibung
Fraunhofer-Gesellschaft is a leading organization for application-oriented research, developing pioneering technologies for economy and society. Applied research in Circular Economy, Carbon Management, Green Hydrogen and Local Energy Systems contributes to UN Sustainable Development Goals.
Noch nicht perfekt?
- Fraunhofer-Gesellschaft
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