PhD Student in Generative Acoustics in Surgery

The Research in Orthopedic Computer Science (ROCS) group at the University of Zurich develops advanced solutions for surgical context understanding training, guidance, and robotics. Our work combines medical imaging, computer vision, and machine learning with strong clinical translation, in close collaboration with Balgrist University Hospital and the national research platform OR-X (OR-X).

We are offering a PhD position in a Swiss National Science Foundation project on Surgical Digital Twins. The goal of this PhD project is to develop data-driven, generative models of surgical acoustics that capture tool–tissue interactions, procedural context, and operating-room soundscapes for multi-modal surgical digital twins.

This position provides a unique opportunity to work at the frontier of computer-assisted orthopedic surgery, embedded in Zurich's vibrant MedTech and AI ecosystem. With direct access to the state-of-the-art OR-X infrastructure for translational validation, the successful candidate will join an innovative team and collaborate with surgeons and industry partners to shape technologies with strong potential for clinical adoption.

Your responsibilities

The PhD student's primary responsibility is to conduct original research at the intersection of signal processing, machine learning, and medical imaging with direct application to orthopedic surgery. The student will focus on the development of generative audio models to create a realistic, action-conditioned soundscape of a surgical procedure and advance the multimodality of current surgical simulations. The work encompasses data collection through ex-vivo experiments, the development of novel scientific methods, their integration into a functional prototype, and its validation in user studies.

The work is expected to produce methodological contributions documented through publications in leading venues such as MICCAI, IPCAI, or Medical Image Analysis. During the initial phase, the candidate will review the state-of-the-art and establish a structured multi-year research plan together with the supervisor. The PhD is embedded in the graduate school of the University of Zurich, which also involves serving as a teaching assistant for 1–2 courses per year.

In particular, the PhD project will involve:

• Advancing the state-of-the-art of generative models to generate action-conditioned realistic soundscapes for the next generation of multimodal surgical simulations
• Developing an advanced data capture setup and acquiring a dataset in a realistic ex-vivo experiment at OR-X
• Benchmarking existing generative approaches to produce a realistic soundscape for surgical tool-tissue interaction
• Performing validation and user studies to evaluate the effectivness of the developed methods
• Collaborating with surgeons and engineers to ensure translational relevance
• Disseminating results through scientific publications, patents, and prototype demonstrations

Your profile

You hold an excellent MSc degree in mechanical, electrical engineering, or computer science, with a strong background in signal processing, machine learning, computer vision, and image processing - ideally in the context of computer-assisted surgery. You bring excellent programming skills, hands-on experience with hardware (e.g., audio capture devices, cameras, tracking systems, imaging devices), and proficiency with software frameworks (OpenCV, Open3D, ROS2, AI/ML libraries).

We are looking for candidates who demonstrate:

• Solid understanding of generative models and proven experience in working with multimodal data (images, 3D data, natural language, audio)
• Familiarity with AI/ML (e.g., PyTorch, TensorFlow) and signal processing (scipy, librosa) frameworks
• Practical experience with computer vision and/or machine listening and proficiency in relevant libraries (e.g., OpenCV, Open3D, librosa, PyAudio)
• Excellent communication skills in English (German is an asset), combined with initiative, problem-solving ability, and teamwork

What we offer

Our employees benefit from a wide range of attractive offers. More

Location

Research in Orthopedic Computer Science (ROCS)

Information on your application

What We Offer

Embedded in the Greater Zurich Area, one of Europe's leading hubs for MedTech and AI innovation, the ROCS group pursues the mission of turning fundamental research into technologies with clinical impact. We offer a supportive and welcoming environment where you can thrive, learn, and grow. The Balgrist Campus, OR-X, and the University of Zurich together provide world-class research infrastructure at the forefront of surgical innovation. This PhD will prepare you for a career in academia, MedTech, or surgical robotics, with strong exposure to both scientific excellence and clinical translation.

We also offer:

• A competitive PhD salary in accordance with SNF guidelines
• A flexible working environment with hybrid (on-site + remote) options
• An inspiring workplace at Balgrist CAMPUS, Lengghalde 5, 8008 Zurich (Balgrist CAMPUS)
• Access to OR-X, a state-of-the-art national research infrastructure shaping the future of surgery (OR-X)
• Opportunities to participate in international conferences and workshops
• Teaching experience and supervision of MSc student research projects

Application

The anticipated start date of the PhD project is spring 2026, with flexibility by mutual agreement. To apply, please submit your motivation letter (1 page) and academic CV as a single PDF file.

Further information

Questions about the job

Matthias Seibold
Stellvertretender Forschungsgruppenleiter ROCS
+41 44 510 73 57
Joinrocs@balgrist.ch

Working at UZH

The University of Zurich, Switzerland's largest university, offers a range of attractive positions in various subject areas and professional fields. With around 10,000 employees and currently 12 professional apprenticeship streams the University offers an inspiring working environment on cutting-edge research and top-class education. Put your talent and skills to work with us. Find out more about UZH as an employer!