PhD Cross-Domain Hyperspectral Anomaly Detection for Manufacturing (fmdiv.)

The future of industrial manufacturing critically depends on the ability to detect even the smallest anomalies with precision and reliability. As a PhD candidate in our team you will play a key role in redefining the boundaries of hyperspectral anomaly detection. You will develop robust AI systems that generalize across different materials and production sites thereby helping to revolutionize quality assurance.

• In this role you will combine cuttingedge fundamental research with direct industrial application and actively shape the next generation of intelligent inspection solutions.
• You will develop and evaluate advanced machine learning methods for hyperspectral anomaly detection leveraging selfsupervised representation learning as well as transfer and metalearning techniques complemented by domain generalization approaches.
• Furthermore you will analyze and process large volumes of hyperspectral data from real industrial applications as well as develop dataefficient and scalable methods.
• As part of our team you will work closely with internal and external partners to transfer research results into practice as well as ensure effective knowledge exchange.
• Last but not least you will publish your research results in renowned scientific journals and present them at international conferences actively contributing to the scientific community.

Qualifications :

• Education: completed Masters degree in computer science machine learning artificial intelligence or a related field with excellent academic performance
• Experience and Knowledge: 
  • solid experience with machine learning methods particularly in the field of deep learning
  • very strong programming skills in Python
  • experience with at least one deep learning framework (e.g. PyTorch or JAX)
  • strong background in computer vision and probabilistic modeling
  • knowledge of representation learning selfsupervised learning or transfer learning
  • interest in digital signal processing physics optics photonics or materials science is a plus
• Personality and Working Practice: you analyze complex research questions with strong analytical skills and develop innovative solutions; you work independently in a structured and goaloriented manner clearly communicate your results and take responsibility for your research; you also collaborate effectively with industrial partners and demonstrate high intrinsic motivation for highquality research in an industrial environment
• Enthusiasm: you have a strong interest in machine learning and computer vision for industrial applications and are passionate about solving challenging realworld problems through research
• Languages: very good German and English skills both written and spoken

Additional Information :

final PhD topic is subject to your university.

Start: according to prior agreement

Please submit all relevant documents (CV letter of motivation certificates and links to GitHub or kaggle account). 

Diversity and inclusion are not just trends for us but are firmly anchored in our corporate culture. Therefore we welcome all applications regardless of gender age disability religion ethnic origin or sexual identity.

Need support during your application
Celina Dannecker (Human Resources)
49 6

Need further information about the job
Alexander Qualmann (Functional Department)

Matthias Kayser (Functional Department)
49 152
Petru Tighineanu (Functional Department)

Work #LikeABosch starts here: Apply now!

Remote Work :

No

Employment Type :

Full-time