Postdoctoral Researcher in Generative AI for Mechanism Design

ETH Zürich

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  • Publication date:

    12 April 2024
  • Workload:

    100%
  • Contract type:

    Permanent position
  • Place of work:

    Zürich

Postdoctoral Researcher in Generative AI for Mechanism Design

Postdoctoral Researcher in Generative AI for Mechanism Design

100%, Zurich, fixed-term

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 fully funded for 2 years.

Ideal starting date: July 2024 (or shortly thereafter).

Project background

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.

In this project, we will work in working in structural, topological and morphological design automation for individuals with pathological gait. You will be the team lead in developing a new design process and additive manufacturing based on simulations of individual walking patterns.

As a team member, you will experience a range of exciting challenges, including the development of innovative technologies for patient usage, and developing standardization methods for customizing aids.

You will be based at ETH Zurich and collaborate with the team at the Swiss Paraplegic Center (SPZ) in Nottwil and an industrial in our shared project.

Job description

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.

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).

Your profile

You have outstanding experience in Machine Learning with a PhD degree from a university in Computer Science, or related fields, with a proven track record in machine learning, deep learning, and topological optimization.

  • Highly motivated, self-driven, and shows excellent performance
  • Strong analytical, mathematical, and algorithmic capabilities
  • Understanding and experience in human modelling and simulation
  • Proficiency in mathematical optimization (e.g. multiobjective GA)
  • Confirmed records on the methodological areas: deep learning, topological design, generative AI (preferred)
  • Proven track record in deploying machine learning models into production (preferred)
  • Proficiency in programming in Python (preferred)
  • Proven record of leading interdisciplinary projects (desirable)
  • Adaptable and flexible to the continuous changes associated with research demands
  • Passion for design and assistive devices

Your workplace

Your workplace

We offer

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 would be arranged between Zurich, Bern and Nottwil with flexibility for some remote work possible. Flexibility to travel is expected within Switzerland.

We value diversity

Curious? So are we.

We look forward to receiving your online application in a single PDF with the following documents:

  • Statement of interests and self-assessment of your profile match (1 page Max) with the subject line: "AI in healthcare is transparent or null"
  • CV (2 pages max)
  • One of your publications on a related topic (linked to open-source code)
  • Names and contact information of 2 references

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. Questions regarding the position should be submitted to Mrs. Ai Sullivan, Email ai.sullivan@hest.ethz.ch (no applications).

About ETH Zürich

Curious? So are we.

We look forward to receiving your online application in a single PDF with the following documents:

  • Statement of interests and self-assessment of your profile match (1 page Max) with the subject line: "AI in healthcare is transparent or null"
  • CV (2 pages max)
  • One of your publications on a related topic (linked to open-source code)
  • Names and contact information of 2 references

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. Questions regarding the position should be submitted to Mrs. Ai Sullivan, Email ai.sullivan@hest.ethz.ch (no applications).

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