- Expertini Resume Scoring: Our Semantic Matching Algorithm evaluates your CV/Résumé before you apply for this job role: Master Thesis: »Machine Learning (ML) Based Methods as Surrogate for Finite Element Modelling«.
 
  
  
    
    
  
      Urgent! Master Thesis: »Machine Learning (ML)-Based Methods as Surrogate for Finite Element Modelling« Job Opening In Aachen – Now Hiring Fraunhofer
 
                        
                          The »« department develops technologies and application-oriented solutions for machining along the entire process chain - from process design and process simulation to real-time data acquisition during production, consulting, and prototype manufacturing.   What you will do
                
Graph neural networks provide an opportunity to operate on Mesh structured data utilized in Finite Element Method (FEM) simulations and offer time-saving benefits.
We are looking for a dedicated and motivated student to assist us in implementing a novel Graph Neural Network based algorithm that can act as surrogate for FEM and accelerate process stability calculation for machining process.
What you bring to the table
What you can expect
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. 
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. 
Interested?
Apply online now.
We look forward to getting to know you!
For any further information on this position please contact:
Aakash Singh M.Sc.
Research Assistant »High Performance Cutting«
Phone: +49 241 8904- 587
Fraunhofer Institute for Production Technology IPT
Requisition Number: 80874 Application Deadline:
✨ Smart • Intelligent • Private • Secure
Practice for Any Interview Q&A (AI Enabled)
Predict interview Q&A (AI Supported)
Mock interview trainer (AI Supported)
Ace behavioral interviews (AI Powered)
Record interview questions (Confidential)
Master your interviews
Track your answers (Confidential)
Schedule your applications (Confidential)
Create perfect cover letters (AI Supported)
Analyze your resume (NLP Supported)
ATS compatibility check (AI Supported)
Optimize your applications (AI Supported)
O*NET Supported
O*NET Supported
O*NET Supported
O*NET Supported
O*NET Supported
European Union Recommended
Institution Recommended
Institution Recommended
Researcher Recommended
IT Savvy Recommended
Trades Recommended
O*NET Supported
Artist Recommended
Researchers Recommended
Create your account
Access your account
Create your professional profile
Preview your profile
Your saved opportunities
Reviews you've given
Companies you follow
Discover employers
O*NET Supported
Common questions answered
Help for job seekers
How matching works
Customized job suggestions
Fast application process
Manage alert settings
Understanding alerts
How we match resumes
Professional branding guide
Increase your visibility
Get verified status
Learn about our AI
How ATS ranks you
AI-powered matching
Join thousands of professionals who've advanced their careers with our platform
Unlock Your Master Thesis Potential: Insight & Career Growth Guide
Real-time Master Thesis Jobs Trends in Aachen, Germany (Graphical Representation)
Explore profound insights with Expertini's real-time, in-depth analysis, showcased through the graph below. This graph displays the job market trends for Master Thesis in Aachen, Germany using a bar chart to represent the number of jobs available and a trend line to illustrate the trend over time. Specifically, the graph shows 1540 jobs in Germany and 26 jobs in Aachen. This comprehensive analysis highlights market share and opportunities for professionals in Master Thesis roles. These dynamic trends provide a better understanding of the job market landscape in these regions.
Great news! Fraunhofer is currently hiring and seeking a Master Thesis: »Machine Learning (ML) Based Methods as Surrogate for Finite Element Modelling« to join their team. Feel free to download the job details.
Wait no longer! Are you also interested in exploring similar jobs? Search now: Master Thesis: »Machine Learning (ML) Based Methods as Surrogate for Finite Element Modelling« Jobs Aachen.
An organization's rules and standards set how people should be treated in the office and how different situations should be handled. The work culture at Fraunhofer adheres to the cultural norms as outlined by Expertini.
The fundamental ethical values are:The average salary range for a Master Thesis: »Machine Learning (ML) Based Methods as Surrogate for Finite Element Modelling« Jobs Germany varies, but the pay scale is rated "Standard" in Aachen. Salary levels may vary depending on your industry, experience, and skills. It's essential to research and negotiate effectively. We advise reading the full job specification before proceeding with the application to understand the salary package.
Key qualifications for Master Thesis: »Machine Learning (ML) Based Methods as Surrogate for Finite Element Modelling« typically include Computer Occupations and a list of qualifications and expertise as mentioned in the job specification. Be sure to check the specific job listing for detailed requirements and qualifications.
To improve your chances of getting hired for Master Thesis: »Machine Learning (ML) Based Methods as Surrogate for Finite Element Modelling«, consider enhancing your skills. Check your CV/Résumé Score with our free Resume Scoring Tool. We have an in-built Resume Scoring tool that gives you the matching score for each job based on your CV/Résumé once it is uploaded. This can help you align your CV/Résumé according to the job requirements and enhance your skills if needed.
 
            Here are some tips to help you prepare for and ace your job interview:
Before the Interview:To prepare for your Master Thesis: »Machine Learning (ML) Based Methods as Surrogate for Finite Element Modelling« interview at Fraunhofer, research the company, understand the job requirements, and practice common interview questions.
Highlight your leadership skills, achievements, and strategic thinking abilities. Be prepared to discuss your experience with HR, including your approach to meeting targets as a team player. Additionally, review the Fraunhofer's products or services and be prepared to discuss how you can contribute to their success.
By following these tips, you can increase your chances of making a positive impression and landing the job!
Setting up job alerts for Master Thesis: »Machine Learning (ML) Based Methods as Surrogate for Finite Element Modelling« is easy with Germany Jobs Expertini. Simply visit our job alerts page here, enter your preferred job title and location, and choose how often you want to receive notifications. You'll get the latest job openings sent directly to your email for FREE!