Bosch Group
Master Thesis Deep Learning for Multi-Channel Vision in Product Manufacturing(m/w/x)
Full-timeInternshipWith Homeoffice
Renningen
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BOBosch Group
PhD - Cross-Domain Hyperspectral Anomaly Detection for Manufacturing(m/w/x)
Renningen
Full-timeWith Home Office
AI/ML
Data Science
Nejo AI Summary
Developing advanced ML for hyperspectral anomaly detection in manufacturing. Deep learning, Python, and PyTorch/JAX experience required. Focus on self-supervised learning and industrial application.
Requirements
- Master’s degree in computer science, machine learning, AI, or related field with excellent academic performance
- Solid experience with machine learning methods, particularly deep learning
- Very strong Python programming skills
- Experience with at least one deep learning framework (PyTorch or JAX)
- Strong background in computer vision and probabilistic modeling
- Knowledge of representation learning, self-supervised learning, or transfer learning
- Interest in digital signal processing, physics, optics, photonics, or materials science (plus)
- Analytical skills for complex research questions and innovative solutions
- Independent, structured, goal-oriented work manner
- Clear communication of results
- Responsibility for research
- Effective collaboration with industrial partners
- High intrinsic motivation for industrial research
- Strong interest in machine learning and computer vision for industrial applications
- Passion for solving real-world problems through research
- Very good German and English skills (written and spoken)
Tasks
- Redefine boundaries of hyperspectral anomaly detection
- Combine fundamental research with industrial application
- Shape next generation of intelligent inspection solutions
- Develop advanced machine learning methods for anomaly detection
- Evaluate self-supervised representation learning techniques
- Apply transfer and meta-learning methods
- Implement domain generalization approaches
- Analyze large volumes of hyperspectral data
- Process industrial application data
- Develop data-efficient and scalable methods
- Collaborate with internal and external partners
- Transfer research results into practice
- Ensure effective knowledge exchange
- Publish research in scientific journals
- Present findings at international conferences
- Contribute to the scientific community
Education
- Master's degree
Languages
- German – Business Fluent
- English – Business Fluent
Tools & Technologies
- Python
- PyTorch
- JAX
- Deep learning
- Machine learning
- Computer vision
- Probabilistic modeling
- Representation learning
- Self-supervised learning
- Transfer learning
- Digital signal processing
- Physics
- Optics
- Photonics
- Materials science
Find the original job posting in its most current version here. Nejo automatically captured this job from the website of Bosch Group and processed the information on Nejo with the help of AI for you. Despite careful analysis, some information may be incomplete or inaccurate. Please always verify all details in the original posting! Content and copyrights of the original posting belong to the advertising company.
Not a perfect match?
- Bosch Group
Promotion (PhD): KI-basierte Lernstrategien für Smart Manufacturing im europäischen HORIZON-Projekt(m/w/x)
Full-timeFreelanceWith HomeofficeNot specifiedStuttgart - TRUMPF Werkzeugmaschinen SE + Co. KG
Praktikum Bildbasierte Feature-Extraktion im Bereich industrieller Bildverarbeitung(m/w/x)
Full-timeInternshipWith HomeofficeDitzingen - Bosch Group
Research Engineer - Reinforcement Learning and Agentic AI(m/w/x)
Full-time/Part-timeWith HomeofficeExperiencedRenningen - TRUMPF Laser- und Systemtechnik SE
Praktikum im Bereich Machine Learning und Computer Vision(m/w/x)
Full-timeInternshipWith HomeofficeDitzingen
BOBosch Group
PhD - Cross-Domain Hyperspectral Anomaly Detection for Manufacturing(m/w/x)
Renningen
Full-timeWith Home Office
AI/ML
Data Science
Nejo AI Summary
Developing advanced ML for hyperspectral anomaly detection in manufacturing. Deep learning, Python, and PyTorch/JAX experience required. Focus on self-supervised learning and industrial application.
Requirements
- Master’s degree in computer science, machine learning, AI, or related field with excellent academic performance
- Solid experience with machine learning methods, particularly deep learning
- Very strong Python programming skills
- Experience with at least one deep learning framework (PyTorch or JAX)
- Strong background in computer vision and probabilistic modeling
- Knowledge of representation learning, self-supervised learning, or transfer learning
- Interest in digital signal processing, physics, optics, photonics, or materials science (plus)
- Analytical skills for complex research questions and innovative solutions
- Independent, structured, goal-oriented work manner
- Clear communication of results
- Responsibility for research
- Effective collaboration with industrial partners
- High intrinsic motivation for industrial research
- Strong interest in machine learning and computer vision for industrial applications
- Passion for solving real-world problems through research
- Very good German and English skills (written and spoken)
Tasks
- Redefine boundaries of hyperspectral anomaly detection
- Combine fundamental research with industrial application
- Shape next generation of intelligent inspection solutions
- Develop advanced machine learning methods for anomaly detection
- Evaluate self-supervised representation learning techniques
- Apply transfer and meta-learning methods
- Implement domain generalization approaches
- Analyze large volumes of hyperspectral data
- Process industrial application data
- Develop data-efficient and scalable methods
- Collaborate with internal and external partners
- Transfer research results into practice
- Ensure effective knowledge exchange
- Publish research in scientific journals
- Present findings at international conferences
- Contribute to the scientific community
Education
- Master's degree
Languages
- German – Business Fluent
- English – Business Fluent
Tools & Technologies
- Python
- PyTorch
- JAX
- Deep learning
- Machine learning
- Computer vision
- Probabilistic modeling
- Representation learning
- Self-supervised learning
- Transfer learning
- Digital signal processing
- Physics
- Optics
- Photonics
- Materials science
Find the original job posting in its most current version here. Nejo automatically captured this job from the website of Bosch Group and processed the information on Nejo with the help of AI for you. Despite careful analysis, some information may be incomplete or inaccurate. Please always verify all details in the original posting! Content and copyrights of the original posting belong to the advertising company.
About the Company
Bosch Group
Industry
Manufacturing
Description
Das Unternehmen entwickelt hochwertige Technologien und Dienstleistungen, die das Leben der Menschen verbessern.
Not a perfect match?
- Bosch Group
Master Thesis Deep Learning for Multi-Channel Vision in Product Manufacturing(m/w/x)
Full-timeInternshipWith HomeofficeRenningen - Bosch Group
Promotion (PhD): KI-basierte Lernstrategien für Smart Manufacturing im europäischen HORIZON-Projekt(m/w/x)
Full-timeFreelanceWith HomeofficeNot specifiedStuttgart - TRUMPF Werkzeugmaschinen SE + Co. KG
Praktikum Bildbasierte Feature-Extraktion im Bereich industrieller Bildverarbeitung(m/w/x)
Full-timeInternshipWith HomeofficeDitzingen - Bosch Group
Research Engineer - Reinforcement Learning and Agentic AI(m/w/x)
Full-time/Part-timeWith HomeofficeExperiencedRenningen - TRUMPF Laser- und Systemtechnik SE
Praktikum im Bereich Machine Learning und Computer Vision(m/w/x)
Full-timeInternshipWith HomeofficeDitzingen