Forschungszentrum Jülich in Germany is recruiting a doctoral researcher to develop advanced machine learning methods for analysing complex scientific images and accelerating materials research.
The project, Representation and Active Learning for Multi-Scale Scientific Imaging, is based at the Institute for Advanced Simulation – Materials Data Science and Informatics (IAS-9). The successful candidate will develop AI methods that can interpret images captured using electron microscopy, recognise patterns across different imaging techniques and guide researchers on which experiments to conduct next. The research will contribute to materials discovery, including collaborative work on sustainable steel development.
Table of Content
Summary
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Benefits
- A creative work environment: A leading research facility, located on an attractive research campus at the TZA Aachen and the Forschungszentrum Jülich. 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
- Networking & Exchange: The opportunity to participate in international conferences and project meetings as well as an opportunity for a fully funded extended international research stay
- 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).
- Annual Leave: You get 30 days of annual leave
- Work-life balance: We offer flexible working hours to help you balance your professional and personal life. You also have the option of flexible working (in terms of location), which is generally possible after consultation and in line with upcoming tasks and (on-site) appointments
- Fair remuneration: Depending on your qualifications and assigned responsibilities, you will be classified according to pay group 13 (80%) of the TVöD-Bund. In addition to the basic salary, there is an additional year-end bonus under the collective pay agreement amounting to 75% of a monthly salary, as well as capital-forming benefits. All information about the TVöD-Bund collective agreement can be found on the BMI website (pay scale table on page 74 of the PDF download).
- Fixed-term: The position is initially for a fixed term of 3 years
- Support for international employees: Our International Advisory Service makes it easier for international employees to get started
Requirements
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.
- Very good command of written and spoken English with extensive vocabulary is required (at least B2 level according to the CEFR), ideally supported by a certificate confirming the language level.
Application Documents
- To apply, please submit a complete CV, letter of motivation, university degree records and certificates.
Application Deadline
Not SpecifiedHow To Apply
For more information, kindly visit the FZ Juelich webpage.
