Team Lead Position in Data-Centric AI

Deutsches Krebsforschungszentrum (DKFZ) -- Team Lead Position in Data-Centric AI

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The German Cancer Research Center (DKFZ) is one of Europe’s largest cancer research centers. “Research for a life without cancer" is the mission of our world-class scientists and all our team members.*
The DKFZ is a place where the brightest minds pursue bold ideas and seek answers to pioneering scientific questions through collaboration, innovation, and exploration across many disciplines. We provide a dynamic environment that empowers excellence with state-of-the-art technologies, cutting-edge infrastructure, and a global scientific network. *
Contribute your knowledge, vision, and dedication to create a space where scientific discovery in cancer research is transformed into benefits for human health.*

As a core partner in Helmholtz Imaging (HI), the German Cancer Research Center is committed to advancing imaging science and technology across all scales, modalities, and scientific domains together with the Max Delbrück Center for Molecular Medicine in the Helmholtz Association (MDC, Berlin), the Helmholtz-Centre for Environmental Research (UFZ, Leipzig), and the German Electron Synchrotron (DESY, Hamburg).

Within HI, DKFZ contributes a strong focus on AI-based image analysis and AI validation, offering an attractive research environment with excellent infrastructure, mentoring for young investigator group leaders, administrative support for extramural funding (e.g. ERC), and an international, collegial, and family-friendly atmosphere.

We are seeking, at the earliest possible date, an excellent researcher with an outstanding scientific record in machine learning and data-driven methods for imaging to fill a

Team Lead Position in Data-Centric AI

Reference number: 2026-0120*
Heidelberg
Full-time
Medical Image Computing

Your Tasks

The Young Investigator Group will complement DKFZ’s image analysis and AI methodology activities by focusing on data-centric AI and robust machine learning for imaging across domains, with applications spanning biomedical imaging and other imaging-intensive fields represented within the Helmholtz Association.

The group’s methodological focus will be on developing algorithms and frameworks that ensure stable and predictable model behavior under real-world variability and perturbations, such as changes in acquisition devices, experimental setups, environmental conditions, domains and populations, as well as noise characteristics and artifacts. Robustness is understood as a key building block toward trustworthy deployment of AI systems in high-stakes scientific, industrial and biomedical applications.

Potential research topics include:

robustness to distribution shifts, domain adaptation, and domain generalization
out-of-distribution detection and modeling
uncertainty estimation
innovative data curation approaches
learning under label noise and weak supervision
synthetic data generation
fairness research
active and interactive machine learning
trustworthy AI validation

The group leader is expected to actively collaborate with HI support and scientific teams at DKFZ, DESY, UFZ and MDC, contributing to Helmholtz Imaging support activities, including direct interaction with Helmholtz researchers as well as the dissemination and reuse of HI solutions across the Helmholtz Association. The role includes contributions to training, knowledge transfer and education (e.g., seminars, lecture series, summer schools, workshops, and supervision of students and early-career researchers), as well as national and international representation of Helmholtz Imaging and DKFZ. In addition, the group leader is expected to contribute, together with other HI teams at DKFZ, to strategic initiatives and to the continuous shaping of the HI mission.

Your Profile

A PhD in computer science, physics, mathematics, or a related discipline with less than 6 years of postdoctoral experience at the time of application (excluding child-rearing periods)
Outstanding scientific record with deep expertise in machine learning, AI, computer vision, and data processing, with experience in collaborative software development
Highly collaborative, open-science mindset, strong self-motivation, and interest in pursuing innovative research at the frontiers of machine learning

We Offer

Excellent framework conditions: state-of-the-art equipment and oppor­tunities for inter­national networking at the highest level
30 days of vacation per year
Flexible working hours
Remuneration according to TV-L incl. occupational pension plan and capital-forming payments
Possibility of mobile work and part-time work
Family-friendly working environ­ment
Sustainable travel to work: subsidized Germany job ticket
Unleash your full potential: targeted offers for your personal development to further develop your talents
Our Corporate Health Manage­ment Program offers a holistic approach to your well-being
Contact:*

Prof. Dr. Klaus Maier-Hein
Phone:

The position is limited to 3 years with the possibility of prolongation.

*Application Deadline: *24.06.2026

Applications by e-mail cannot be accepted.
Please also note that we cannot return applications submitted by post.

Are you interested?

Then become part of the DKFZ and join us in contributing to a life without cancer!

[Apply now](

We are convinced that an innovative research and working environment thrives on the diversity of its employees. Therefore, we welcome applications from talented people, regardless of gender, cultural background, nationality, ethnicity, sexual identity, physical ability, religion and age. People with severe disabilities are given preference if they have the same aptitude.

*Notice:* We are subject to the regulations of the Infection Protection Act (IfSG). Therefore, all our employees must provide proof of immunity against measles. xtyydxe

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Deutsches Krebsforschungszentrum | Im Neuenheimer Feld 280 | 69120 Heidelberg | [

Deutsches Krebsforschungszentrum (DKFZ)

2026-06-24T21:59:59Z FULL_TIME
EUR
YEAR null

2026-06-05

Heidelberg 69120 Im Neuenheimer Feld 280

49.4143686 8.6723038