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
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