PhD-student: Machine Learning for Metamaterials
Are you interested in artificial intelligence and in material design? The University of Amsterdam and the AMOLF institute are seeking excellent, highly motivated PhD candidates to enhance metamaterial research using machine learning.
The extraordinary properties of mechanical metamaterials stem from their architecture, or internal structure, rather than their chemical composition. These properties can go beyond (=”meta”) their ingredient materials, and vigorous activities have recently produced programmable and exotic material properties as well as unprecedented mechanical functionalities such as shape-morphing and self-folding. However, understanding how these properties emerge and how we can rationally design metamaterials remain major challenges: how and why mechanical metamaterials function is not well understood, and the design of metamaterials is mostly based on creativity, heuristics and trial-and-error. In this PhD project, we propose to apply machine learning (ML) to force breakthroughs in these key challenges.
• to classify and design the zero modes of metamaterials.
• to predict and design the linear response of metamaterials;
• to make a step towards mechanical logic and computation.
About the group
The Faculty of Science has a student body of around 6,500, as well as 1,600 members of staff working in education, research or support services. Researchers and students at the Faculty of Science are fascinated by every aspect of how the world works, be it elementary particles, the birth of the universe or the functioning of the brain.
The PhD project will be carried out at the Institute of Physics of the University of Amsterdam (UvA) and at the AMOLF institute both located at the Amsterdam Science Park. The project will be jointly co-supervised by Corentin Coulais (UvA), Marjolein Dijkstra (AMOLF/Utrecht University) and Martin van Hecke (AMOLF/Leiden University). Both laboratories focus on Mechanical Metamaterials and benefit from exceptional scientific environments, in soft matter, computational physics and artificial intelligence.
• You will need to meet the requirements for a Master’s degree in physics, mathematics, engineering, computational science or a related field;
• a strong background in physics, for numerical simulations, theory and/or artificial intelligence;
• excellent written and oral communication skills in English.
Terms of employment
A temporary contract for 38 number of hours per week for the duration of 4 years (initial appointment will be for a period of 18 months and after satisfactory evaluation it can be extended for a total duration of 4 years) and should lead to a dissertation (PhD thesis). We will draft an educational plan that includes attendance of courses and (international) meetings. We also expect you to assist in teaching undergraduates and master students.
The salary, depending on relevant experience before the beginning of the employment contract, will be €2.325 to €2.972 (scale P) gross per month, based on fulltime (38 hours a week), exclusive 8 % holiday allowance and 8.3 end-of-year bonus. A favorable tax agreement, the ‘30% ruling’, may apply to non-Dutch applicants. The Collective Labour Agreement of Dutch Universities is applicable.
Are you curious about our extensive package of secondary employment benefits like our excellent opportunities for study and development? Take a look here.
Prof. dr. Martin van Hecke
Prof. Marjolein Dijkstra
The UvA is an equal-opportunity employer. We prioritise diversity and are committed to creating an inclusive environment for everyone. We value a spirit of enquiry and perseverance, provide the space to keep asking questions, and promote a culture of curiosity and creativity.
Do you recognize yourself in the job profile?
• a motivation letter and CV;
• a pdf version of your MSc thesis (or if not finalized yet, an abstract);
• if applicable, pdf versions of your scientific publications and
• the name and email address of at least two referees, who will be asked to upload their recommendation letters.