Bachelor-/ Master Thesis: Deep Learning and Machine Learning in Production
Job Description
The Fraunhofer Institute for Production Technology IPT is seeking motivated students for a Bachelor’s or Master’s thesis focused on the application of Deep Learning (DL) and Machine Learning (ML) in various production scenarios. In the realm of production, there are numerous use cases where DL and ML have been successfully implemented, including the manufacturing of rockets, stem cells for combating blood cancer, optics, and lightweight components. You will engage in creating DL and ML pipelines tailored for specific applications within our industry projects. This thesis provides a unique opportunity to work directly on the integration of these advanced technologies into real-world production settings while collaborating with experts in the field. Your responsibilities will include preparing and processing image and tabular data, implementing DL and ML models based on the specific use case, comparing DL and ML methods with traditional data analysis techniques, and validating as well as documenting the findings of your research.
Key Responsibilities
As part of your thesis, you will undertake the following tasks:
- Prepare and process image data and tabular data in collaboration with experts
- Implement DL and ML models based on specific application requirements
- Compare DL and ML-based methods with classical data analysis techniques
- Validate and document the results of your research
Required Technical Skills
Soft Skills
Qualifications
- Studying Computer Science, Mechanical Engineering, or a related field
- Self-motivation to explore new topics
- Proficient in both German and English
Language Requirements
Programming Languages:
Python, R
Spoken Languages:
English, German
Benefits & Perks
- ✓ Access to state-of-the-art machines and equipment
- ✓ Collaboration within a motivated and interdisciplinary team
- ✓ Creative work environment
Working Conditions
Full Time
Company Culture
The company fosters an inclusive environment that values diverse competencies and encourages innovation. They are committed to the professional growth of their employees and provide opportunities for collaboration and knowledge sharing.
Salary Range
Project Types: Not Available
Career Growth: Potential for future employment post-thesis, Opportunities to engage in additional research projects, Networking within the industry