Research Data Manager (m/f/d) – Clinical AI Infrastructure

Research Data Manager (m/f/d) – Clinical AI Infrastructure

at the Else Kröner Fresenius Center for Digital Health

The position is available from October 1, 2026, full- or part-time, initially limited to 24 months, with the option of extension and longer-term collaboration. Compensation is based on the applicable collective bargaining agreement and, subject to fulfillment of the personal requirements, may be classified according to pay grade E13 .

The position is embedded in an interdisciplinary and international research environment within the Else Kröner Fresenius Center for Digital Health at TU Dresden. While the institute has a strong focus on AI, this position has a broader clinical AI infrastructure mandate and will support projects across the center and its clinical partners that require access to routinely generated clinical data, prospective model evaluation, and robust research software and data infrastructure. The position is embedded into groups working at the intersection of AI development, clinical care, and translational research, with the goal of developing and clinically evaluating AI tools that improve patient care. These groups currently lead several externally funded projects involving large-scale surgical video data, electronic health record data, and multicenter clinical datasets.

As Data Manager/Research Data and Software Engineer, you will play a central and cross-cutting role across clinical AI projects. This is a hands-on data, software, and infrastructure role. Your work will help establish secure access to live or near-real-time clinical data, enable prospective shadow-mode evaluations (“shadow trials”) of AI models without influencing clinical decision-making, and build and maintain reusable research infrastructure. You will ensure that multimodal data along patients treatment pathways are reliably linked, securely stored and managed, and made available to researchers in a well-organized, privacy-compliant, and reproducible manner.

Your responsibilities:

Design, implement, and maintain data pipelines that integrate multimodal, structured and unstructured clinical and surgical data from proprietary data collection systems and electronic health record systems, supporting both retrospective analyses and secure live or near-real-time data flows in coordination with the local data integration center at TU Dresden

Develop and maintain interfaces with clinical data systems using established healthcare interoperability standards, in particular FHIR, and support reliable event-driven or scheduled data exchange for clinical AI applications

Establish and operate workflows for prospective shadow-mode evaluations (“shadow trials”), including automated model execution on live or near-real-time data, model and data versioning, logging, performance monitoring, and audit-ready capture of results without affecting clinical care

Implement and maintain automated and semi-automated workflows for data de-identification and anonymization of clinical patient data, including video and image data, in compliance with applicable data protection regulations (GDPR and hospital data privacy requirements)

Oversee and further develop the institutes data infrastructure, including databases and storage systems, organization, access control, backup procedures, long-term archiving, and documentation of clinical, imaging, video, and model-output datasets according to FAIR principles

Build, maintain, and document reusable r