Are you a highly motivated and enthusiastic researcher looking to make a difference in the field of AI applied in Healthcare? Join us at the Spinal Cord Injury Artificial Intelligence - SCAI Lab at ETH Zurich.
Our team of clinical and research scientists is dedicated to improving healthcare systems using physiological and clinical information analysis for a closed-loop decision support systems in rehabilitation in many health conditions.
This position is open for a postdoctoral researcher in the field of generative design for exoskeletons and orthosis. Focused on developing a novel method for autonomous design of 3D shapes fitting to the user body and optimizing the design to the desired assistance.
Apart from actively shaping our group's research, the positions include international collaboration with partners in Switzerland with academia, clinics and industry, mentoring MSc, and PhD students.
Dr Diego Paez-Granados in collaboration with Prof. Robert Riener (SMS Lab) will supervise the successful researcher.
The position is funded for one year, with possible extension to 2 years.
Ideal starting date: Jan 2026 (or shortly thereafter).
The goal of this project is to leverage advanced machine learning to develop an automated design process of mechanical walking aids, analyse gait patterns, and make biomechanical simulations embedded in the generative mechanism design process.
As a team member, we value an active role in integrating into our group, experiencing a range of exciting challenges, including the development of innovative technologies for patient usage and developing standardisation methods for customising aids.
In this project, we invite applicants interested in coordinating and leading a team of researchers. Coordinating with stakeholders and the research team to develop a new design process and additive manufacturing approach based on simulations of individual walking patterns.
This postdoctoral position would focus on studying shape parametrization, learning gait optimization functions for mechanism design and using different machine learning embeddings (such as GANS, VAEs, and Diffusion Models) for developing a new full pipeline in design.
If you are a highly motivated and creative individual with a passion for innovation, we want to hear from you.
Project leadership & coordination: Plan and deliver work packages, manage timelines, risks, and align milestones across academia and industry.
Supervision & mentoring: Co-supervise MSc and PhD students; run code/design reviews; foster a collaborative, high-standards research culture.
Method development: Shape parameterisation; learning objective functions for mechanism design; build end-to-end pipelines using embeddings and generative models (e.g., GANs, VAEs, Diffusion).
Clinical & industrial translation: Drive standardisation for customised aids; prepare prototypes for patient-facing evaluation and additive manufacturing.
Communication & dissemination: Present to diverse stakeholders; write papers, preprints, and technical reports; contribute to grant deliverables.
In general, postdoctoral researchers at ETH Zurich have a full-time employment. A part-time employment may only be considered in exceptional cases (e.g. child- or familycare, other projects or employment).
You have outstanding experience in Machine Learning with a PhD degree from a university in Computer Science, or related fields,
You will join a team of clinical and research scientists in the task of improving healthcare systems through physiological and clinical data systems design and analysis.
We offer a full-time research position funded with a competitive salary in accordance with ETH standards.
Working location: Swiss Paraplegic Research, Nottwil , with some flexibility for remote work possible accordingly to ETH policy.
Flexibility to travel is expected within Switzerland.
Working, teaching and research at ETH Zurich
We look forward to receiving your online application in a single PDF with the following documents:
Please note that we exclusively accept applications submitted through our online application portal. Applications via email or postal services will not be considered.
Applications will be revised until the position is filled.
Further information about HEST can be found on our website.
In your application, please refer to Professorpositions.com