Bosch

PhD Hyperspectral Anomaly Detection for Manufacturing

Renningen, BW
Python PyTorch JAX Machine Learning Deep Learning Computer Vision AI
Description

PhD - Cross-Domain Hyperspectral Anomaly Detection for Manufacturing (f/m/div.)

Location: Renningen, BW, de

Company Description

At Bosch, we shape the future by inventing high-quality technologies and services that spark enthusiasm and enrich people’s lives. Our promise to our associates is rock-solid: we grow together, we enjoy our work, and we inspire each other. Join in and feel the difference.

The Robert Bosch GmbH is looking forward to your application!

Job Description

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 cutting‑edge 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 self‑supervised representation learning as well as transfer and meta‑learning 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 data‑efficient 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 Master’s 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, self‑supervised 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 goal‑oriented manner, clearly communicate your results, and take responsibility for your research; you also collaborate effectively with industrial partners and demonstrate high intrinsic motivation for high‑quality 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 real‑world problems through research
  • Languages: Very good English skills required; German is a plus

Additional Information

https://www.bosch-ai.com
www.bosch.com/research

The 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)
+49 711 811 21346

Need further information about the job?
Alexander Qualmann (Functional Department)
+49 173 7647721
Matthias Kayser (Functional Department)
+49 152 02116397
Petru Tighineanu (Functional Department)
+49 173 3663911

Work #LikeABosch starts here: Apply now!

Bosch
Bosch

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