Scientist – Curation of annotated X-ray CT images for deep-learning-based segmentation of soil microstructure

The job

We are seeking a scientist (f/m/x) to curate a comprehensive collection of annotated X-ray CT images for deep-learning-based segmentation of soil microstructure within a DFG-funded project. The project aims to bring together a network of experts to jointly build a large dataset of annotated soil microstructure for training AI-based segmentation models and to publish the datasets and models according to FAIR and CARE principles. The scientist will be supported by the Research Data Management team of the UFZ.

Place of work

Halle (Saale)

Working time

100% (39 h/week)

The job position is available for full-time or part-time employment.

Contract limitations

limited contract / 30.06.2028 (18 month)

Salary

Remuneration according to the TVöD public-sector up to pay grade 13 including attractive public-sector social security benefits.

Contact

Your contact for any questions you may have about the job:
Prof. Dr. Steffen Schlüter
steffen.schlueter[at]ufz.de

Your application

To ensure a fair selection process, please submit your application (cover letter, CV, and relevant supporting documents) via our online portal without a photo, age information, or details about your marital status.

Diversity and Inclusion

The UFZ values diversity and is actively committed to ensuring equal opportunities for all employees, regardless of their origin, religion, beliefs, disability, age or sexual identity.
We welcome people who represent diverse backgrounds, identities and perspectives. We therefore particularly encourage people who are affected by structural discrimination to apply to us.

The UFZ

The Helmholtz Centre for Environmental Research (UFZ) is a world-leading institution in environmental research and a member of the Helmholtz Association, Germany’s largest scientific organisation. With approximately 1,200 employees across Leipzig, Halle, and Magdeburg, we have been conducting research since 1991 using a transdisciplinary approach to address the most pressing challenges of our time: biodiversity loss, climate change, and environmental pollution. Our goal is to translate excellent research into practical solutions for policymakers, business, and society, and to serve as a reliable partner in supporting transformation processes toward a sustainable and just future for current and future generations. We foster a culture of collaboration, openness, and diversity within a work environment that actively promotes creativity and personal development.

The job

We are seeking a scientist (f/m/x) to curate a comprehensive collection of annotated X-ray CT images for deep-learning-based segmentation of soil microstructure within a DFG-funded project. The project aims to bring together a network of experts to jointly build a large dataset of annotated soil microstructure for training AI-based segmentation models and to publish the datasets and models according to FAIR and CARE principles. The scientist will be supported by the Research Data Management team of the UFZ.

Your tasks

• Plan, organize, and conduct workshops for need analysis, tutoring image annotations and tutoring semantic image segmentation
• Communication with data owners
• Soil sampling and annotation of underrepresented soils
• Development of learning material and documentation
• Quality control of training data and segmentation model results
• Publish data and models in online repositories by FAIR & CARE principles together with the RDM team
• Publish and present project results in scientific journals, at project meetings and conferences
• Provide scientific guidance and support to interns, PhD students, research assistants, and other staff members

We offer

• The freedom to master even the most demanding challenges between basic research and practical application
• The chance to work in interdisciplinary, international teams and benefit from a variety of perspectives
• Firstclass integration into national and international research networks to work together on global challenges
• Excellent research infrastructure and research data management to optimally support your work
• Flexible working hours and a wide range of options for balancing work and care responsibilities through our family office
• Competent support and advice for international colleagues arriving at the UFZ from the 'International Office'
• Special annual payment, capital-forming benefits and subsidised Germany Job Ticket
• A workplace in a vibrant region with a high life quality and social and cultural diversity

Your profile

• University degree in environmental science, agriculture, image processing or related subjects
• Sound knowledge of soil science
• Knowledge and experience in the interpretation of scientific results
• Experience with X-ray CT and image processing
• Proficiency in Python Coding
• Excellent oral and written communication skills (German and English)
• Ability to work independently and as part of a team

Apply now

Application deadline: 19.10.2026

More information about jobs at the UFZ:
www.ufz.de/career

LinkedIn @UFZ

Family Support

International Office

Accessibility

Diversity, Equity & Inclusion

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