Institute of RemunerationEG 13 ID: 3526WE1 Start of employment: 01.06.2026 Application deadline: 28.02.2026 Scope: part time (82,50%, full-time employment possible); fixed-term employment for 48 months

The DFG-funded Research Training Group (RTG) “Multiscale Imaging and Analytics of Interfaces in Musculoskeletal Health” brings together an interdisciplinary team of researchers from the University Medical Center Hamburg-Eppendorf (UKE), Hamburg University of Technology (TUHH), DESY (PETRA III), and Helmholtz-Zentrum Hereon. We combine cutting-edge imaging, experimental analytics, data science, and translational medicine to visualize, understand and predict how musculoskeletal interfaces form, adapt, fail, or regenerate.

PhD candidates are working in one of the projects at . In total, we are hiring 10 PhD candidates for the first cohort of the RTG, running for 4 years from 2026-2030. Project P7 will be allocated at the Institute of Medical Technology and Intelligent Systems at TUHH, which focuses on AI methods for medicine, particularly machine learning, medical robotics and navigation, image guidance, and treatment planning.

The project, titled "Development of spatiotemporal deep learning methods for shear-wave elastographic imaging at soft tissue interfaces", will establish deep learning-based methods to obtain quantitative estimates of soft tissue elasticity at high spatial and temporal resolution. For further information and , please visit the .

The RTG fosters a vibrant, collaborative, and international research environment – right in the heart of Hamburg’s rapidly growing life-science ecosystem. In addition to access to world-class research facilities, this position offers a unique profile, including annual winter and summer schools, start-up classes, and an international scientific network.

YOUR TASKS

Developing and evaluating deep learning methods for elastographic image processing
Optimizing OCT and ultrasound shear wave image acquisition
Collaborating with different partners, including at a clinics
Systematic experimental evaluations, including on realistic data and using robots
Presentation of your results at top-tier international conferences and publication in high-ranking journals

YOUR PROFILE

Requirements

Completed scientific university studies, in particular in the subject area computer science, robotics, or related engineering fields

Desired knowledge and personal skills

Very good programming skills (Python, C++)
Excellent knowledge of machine learning methods and frameworks
Expertise in robotics, medical imaging, medical image processing & machine learning; particularly for OCT and ultrasound
Excellent English and scientific writing skills; German is a plus
A collaborative mindset and prior experience in academic publishing

OUR OFFER

Scientific qualification with the objective to pursue a PhD
A job in an interesting, friendly and appreciative working environment
Intensive induction/ onboarding
Comprehensive training and further education programs

At the heart of TU Hamburg’s research, teaching and transfer of technology is the guiding principle of developing technology for people. The TU Hamburg sees itself in this context as a family-friendly and sustainable university with high performance and quality standards that strives for excellence in all its research fields. Interdisciplinarity, innovation, regionality and internationality are binding principles in our actions. With currently around 8.000 students, 110 professors and 1.650 employees, the TU Hamburg is characterised by short decision-making processes and close cooperation between the board, the institutes, the deans of studies, the research areas and the administration. We identify ourselves with a modern leadership culture and cultivate appreciative interaction.

For further information please contact Prof. Alexander Schlaefer , Tel.-Nr. +49 40 30601 3050, Email: .

We value diversity, therefore all applications are welcome, regardless of gender, gender identity, ethnic origin, nationality, age, religion and belief, disability, sexual orientation and identity or social background.

The TU Hamburg stands for as well as

Please send your complete application documents (cover letter, curriculum vitae in table form, proof of completed training and/or university degree, job references or certificates of employment) via the online application system.

Notice for graduates of foreign educational qualifications:
Please submit proof of all obtained university degrees and, if available, the recognition of your educational qualifications in Germany (e.g. anabin excerpts and/or acknowledgement of previous employers).