Can an elastic structure get out of a maze, without any control computer, just by snapping, bending and buckling? Can we build robots that have no electronics or hydraulics, yet still behave smart?

Elastic structures can bend or snap under stress – a phenomenon that sometimes results in collapse. As a consequence, buckling has mostly been studied with the goal of avoiding it. However, snapping structures have complex dynamics with multiple stable configurations, similar to the states of a computer. Therefore, they can be used for sensing and processing – to build a mechanical brain that can autonomously react to stimuli.

Designing robotic structures is a very hard problem. The dynamics are governed by nonlinear continuum mechanics, and therefore are computationally difficult to simulate. The design problem – finding a structure that performs in a desired way – is even harder. As a consequence, present-day robotic structures that are designed by hand perform only simple repetitive motions. The goal of this Ph.D. is to design elastic structures that autonomously perform sophisticated tasks. To do this, we will construct optimization algorithms capable of coming up with smarter structures. Before we can start, though, we need a way to describe what the structure should do: a mechanical programming language. Mechanical source code will then be used as input of the optimization software that we will develop.

A ‘mechanical programming language’ must be expressive enough to be able to describe any behavior that our structure should perform, simple enough that a person can write code for it, and designed in such a way so that it can be compiled (automatically translated to a structural design) in reasonable time. During your thesis, you will answer the following questions: How should a programming language be, so it can describe the behavior of a soft robotic structure? How can we efficiently simulate a given source code, to check that it works as expected? How can we ‘compile’ the code into a structure that can be fabricated? While we have promising ideas on how to tackle these questions, you will have the opportunity to try your own approaches and have an impact on the outcome. The focus of this Ph.D. position is theoretical. However, the structures will be fabricated and involvement in the experiment is possible. 

The ideal candidate will combine a strong interest in algorithms and programming (we use Python and C++, but prior experience with these languages is not mandatory) with a background in continuum mechanics including nonlinear Finite Element Analysis. During your Ph.D., you will develop interdisciplinary expertise combining mechanics and computer science. There may be opportunities to intern in computer science departments in the Netherlands or abroad. You will also develop scientific leadership skills through co-supervision of Master students.

You will need to meet the requirements for an MSc-degree, to ensure eligibility for a Dutch PhD examination. The applicant should have a bachelor's and master's degree in physics, math or a relevant engineering discipline (mechanics, electronics, computer science, aerospace).

The position is intended as full-time (40 hours / week, 12 months / year) appointment in the service of the Netherlands Foundation of Scientific Research Institutes (NWO-I) for the duration of four years, with a starting salary of gross € 2,441 per month and a range of employment benefits. After successful completion of the PhD research a PhD degree will be granted. Several courses are offered, specially developed for PhD-students. AMOLF assists any new foreign PhD-student with housing and visa applications and compensates their transport costs and furnishing expenses.

Hypersmart Matter

The hypersmart matter group investigates the processing of information by structured elastic materials. We combine a fundamental interest to understand the limits and principles that govern information processing in physical systems with an applied drive to answer the low-energy and ubiquitous computing needs of the future. To achieve these goals, we combine advanced simulation and design methods with cleanroom fabrication techniques.