PhD position in Machine Learning Directed Design of Actuators from Biological Muscle

Updated: 8 months ago
Job Type: Permanent
Deadline: The position may have been removed or expired!

100%, Zurich, fixed-term

We are looking for a an individual interested in pursuing a PhD at the interface of computational modeling and bioengineering. You will join a group that is working on the next frontier of soft robotics: biohybrid robotics. We focus on engineering skeletal and cardiac muscle tissues to grow biological muscles that are functional and could be used as actuators. These biohybrid systems also provide crucial insight for biomedical topics such as muscle and nerve regeneration, medical implants, and prostheses.

However, the field is currently hindered by a time and resource intensive trial-and-error approach to biofabrication of engineered muscle tissues. Therefore, you will work as an integral part of our biohybrids team on leveraging the power of machine learning and computational modeling to streamline engineered muscle design and computationally capture the complex interplay between biofabrication parameters and the resulting functionality of the contractile muscle construct.


Job description

You will join the efforts of a SNF Sinergia consortium focused on Machine-learned Design and Bioxolography of Functional 3D Skeletal Muscle Tissues. The consortium consists of 4 research groups within Switzerland and Germany, with expertise in cell biology, muscle tissue engineering, and volumetric 3D printing techniques. Our group's expertise fits in on the computational modeling and tissue and mechanical engineering aspects of the project. As such, the research will be inherently collaborative and interdisciplinary. Your role will be mostly computational, but will also involve some amount of biofabrication and work in the laboratory. 

Aside from the Sinergia consortium, you will also support the efforts of the ALIVE Initiative of ETH Zürich which aims to elucidate and apply the design principles of living systems as a basis for sustainable, intelligent, and resilient materials and technologies of the future. Our approach encompasses studying natural systems and developing biohybrid or biomimetic synthetic systems bridging across scales, from the nano to the macro and structural scale. The Soft Robotics Lab is an integral part of the ALIVE Biohybrid Project Stream .

The output of your Ph.D. thesis is going to be highly relevant as a demonstration of directed design of engineered muscle tissues, having impact in the fields of biohybrid robotics as well as the biomedical community as a whole.


Your profile
  • We are looking for a highly motivated, outstanding individual that is curious to continuously consider perspectives of different fields and work to bring the power of computational modeling and machine learning to biofabrication.
  • We particularly value diligence, perseverance, and curiosity in your day to day scientific work.
  • Ideally, you have a strong background in computational modeling and machine learning, with a strong interest in learning key aspects of biofabrication techniques, as well as working with and understanding the challenges of muscle bioengineering. 
  • You should have a computer science or engineering background, with an MSc degree in mechanical, electrical, biomedical engineering, bioengineering, computer science, applied physics, or a related field. 


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We offer

ETH Zurich is a family-friendly employer with excellent working conditions. You can look forward to an exciting working environment, cultural diversity, and attractive offers and benefits.

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Curious? So are we.

We look forward to receiving your online application with the following documents:

  • Cover letter with a description of your research achievements and research interests
  • Detailed CV
  • Transcripts of all degrees (English)
  • Names and contact information of at least three references
  • Representative published research work (Papers, thesis if possible)

Please submit the following application documents using only the ETH online portal in a single merged PDF document, titled with your last name and initials as well as the application date (for example, 20230601_DoeJane_application) in the following order:

Further information about our group can be found on our website . Questions regarding the position should be directed to Federica Poltronieri, email [email protected] (no applications).


About ETH Zürich

ETH Zurich is one of the world’s leading universities specialising in science and technology. We are renowned for our excellent education, cutting-edge fundamental research and direct transfer of new knowledge into society. Over 30,000 people from more than 120 countries find our university to be a place that promotes independent thinking and an environment that inspires excellence. Located in the heart of Europe, yet forging connections all over the world, we work together to develop solutions for the global challenges of today and tomorrow.



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