Your Job:

The PhD project is methodologically independent and embedded in a multidisciplinary research environment at the interface of artificial intelligence, scientific imaging, and materials research. You will strengthen the data science and machine learning activities of IAS-9 by developing core AI methods with applications to electron microscopy and materials discovery. You will work in a team of data scientists, software engineers, and experimental researchers on topics including:

• Developing multi-scale and multi-modal representation learning methods for scientific imaging data (e.g., SEM, TEM, EBSD).
  
• Learning representations that are robust to scale changes, modality shifts, and domain differences across instruments and laboratories.
  
• Designing active learning and experimental design strategies that use learned representations to guide data acquisition under cost and uncertainty constraints.
  
• Building surrogate models that connect imaging-derived representations with downstream physical or functional properties.
  
• Collaborating closely with experimental partners to integrate decision-making algorithms into real scientific workflows.
  
• Publishing results in high-impact machine learning and interdisciplinary journals and conferences, and contributing to open-source research software.
  

The developed methods will be validated using large-scale electron microscopy data from collaborative research projects, including an EU-funded project on sustainable steel development, while maintaining a clear focus on fundamental AI research questions.

Your Profile:

We are looking for a highly motivated candidate with a strong interest in foundational machine learning research and its application to real-world scientific problems. You should bring:

• A completed university degree (Master or equivalent) in computer science, data science, applied mathematics, physics, materials science, or a related field.
  
• Solid background in machine learning and/or computer vision.
  
• Interest in representation learning, active learning, uncertainty modeling, or decision-making under constraints.
  
• Experience with Python and modern ML frameworks such as PyTorch or TensorFlow.
  
• Curiosity for interdisciplinary research; prior experience with scientific or microscopy data is welcome but not required.
  
• Strong analytical skills, scientific creativity, and the ability to work independently while collaborating in a team environment.

Our Offer:

We work on the very latest issues that impact our society and are offering you the chance to actively help in shaping the change! We support you in your work with:

RESEARCH & INFRASTRUCTURE: The opportunity to conduct exciting research in an international and multidisciplinary environment with outstanding infrastructure and to strengthen your reputation in a dynamic and highly active research field
ENVIRONMENT: A creative work environment at a leading research facility, located on an attractive research campus at the TZA Aachen https://tza-aachen.de and the Forschungszentrum Jülich
NETWORKING & EXCHANGE: The opportunity to attend national and international conferences and actively build your scientific network
KNOWLEDGE & DEVELOPMENT: Your professional development is important to us - we support you specifically and individually e.g., through training and networking opportunities specifically for doctoral candidates (JuDocS): https://go.fzj.de/JuDocs
SUPPORT FOR INTERNATIONAL EMPLOYEES: Our International Advisory Service makes it easier for international employees to get started
FAIR REMUNERATION: Depending on your qualifications and assigned responsibilities, you will be classified according to pay group 13 (80%) of the TVöD-Bund. Additionally, you will receive a special payment ("Christmas bonus”) amounting to 60% of one month’s salary. All information about the TVöD-Bund collective agreement can be found on the BMI website (pay scale table on page 69 and following of the PDF download): https://go.fzj.de/bmi.tvoed
FIXED-TERM: The position is limited to 3 years

In addition to exciting tasks and a collegial working environment, we offer you much more: https://go.fzj.de/benefits

To apply, please submit a complete CV, letter of motivation, university degree records and certificates.

Place of employment: Jülich/Aachen

We welcome applications from people with diverse backgrounds, e.g. in terms of age, gender, disability, sexual orientation / identity, and social, ethnic and religious origin. A diverse and inclusive working environment with equal opportunities in which everyone can realize their potential is important to us.

The following links provide further information on diversity and equal opportunities: https://go.fzj.de/equality and and on the targeted promotion of women: https://go.fzj.de/womens-job-journey