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PhD-student: Active Hysterons and Spiking Neurons for Physical Computing

Work Activities

We are seeking a motivated PhD- student to join our teams working on bistable elements for in-materia computing, as part of a joint theoretical/experimental program carried out at AMOLF (Amsterdam) and TU/e (Eindhoven).

Computing with artificial neurons takes inspiration from nature’s efficient, adaptive use of multistable networks, offering an alternative to energy-intensive digital systems with rigid bits and separated memory and computation. In this project, we aim to design and realize the first networks combining active and passive electronic neurons, using organic electronics for chemical and electrical tunability. This work is based on recent breakthroughs in our groups.
The Van Hecke group recently showed that passive, bistable hysterons excel at sequential tasks such as counting1,2, whereas the group of van de Burgt has built active electronic neurons that mimic spiking3,4. Surprisingly, we found that spiking neurons can be described as ‘active’ hysterons, forming a bridge between two distinct frameworks for in-materia computing. Hence, by combining active and passive elements we aim to combine the best of both worlds, endowing passive networks with adaptability and spiking networks with memory and sequencing. We will explore the computational power of these systems and demonstrate it in simple robots. Our work bridges organic neural systems and hysteron computing, and leverages (bio)chemical and electrical feedback to materialize adaptivity and plasticity.

Key questions include: How to realize and design mixed networks of passive and active artificial neurons? How do mixed networks extend the class of realizable computing? Do our networks exhibit spiking, bursting or synchronization, and how to control these behaviors? How to realize targeted sequential and adaptive computations? Can we develop neuronal circuits for maze-solving and sequential adaptation? To answer these questions, the project will involve computational modelling and experimental work, jointly supervised by Martin van Hecke and Yoeri van de Burgt. With this research, we aim to redefine physical computation.

To get an idea of our work, see:

[1] Kwakernaak and van Hecke, Counting and Sequential Information Processing in Mechanical Metamaterials, PRL 130 268204 (2023)

[2] Liu, Teunisse, Korovin, Vermaire, Jin, Bense and van Hecke, Controlled Pathways and Sequential Information Processing in Serially Coupled Mechanical Hysterons, PNAS 121, e2308414121 (2024).
[3] Matrone, van Doremaele, Surendran, Laswick, Griggs, Ye, McCulloch, Santoro, Rivnay and van de Burgt, A modular organic neuromorphic spiking circuit for retina-inspired sensory coding and neurotransmitter-mediated neural pathways, Nat Comm 15, 2868 (2024)

[4] Gkoupidenis, Zhang, Kleemann, Ling, Santoro, Fabiano, Salleo and van de Burgt, Organic mixed conductors for bioinspired electronics, Nat Rev Mat 9, 134 (2023)

[5] Baconnier, Teunisse and van Hecke, Dynamic self-loops in networks of passive and active binary elements, arXiv:2412.12658

Qualifications
We seek candidates with a strong background in physics, electrical\mechanical engineering, materials science, or computer science with an interest in complex materials for computing and learning. Excellent candidates with training in any area of science or engineering will be considered. PhD candidates must meet the requirements for an MSc degree. Good verbal and written communication skills in English are required. Other advantageous qualities include experience with coding (Python\Matlab) and numerical methods, as well as familiarity with concepts in complex systems, physical memories or machine learning. We strongly believe in the benefits of an inclusive and diverse research environment, and welcome applicants with any background.

Work environment
AMOLF is a part of NWO-I and initiate and performs leading fundamental research on the physics of complex forms of matter, and to create new functional materials, in partnership with academia and industry. The institute is located at Amsterdam Science Park and currently employs about 140 researchers and 80 support employees. www.amolf.nl

Working conditions

  • The working atmosphere at the institute is largely determined by young, enthusiastic, mostly foreign employees. Communication is informal and runs through short lines of communication.
  • 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
  • The starting salary is 2.968 Euro’s gross per month and a range of employment benefits.
  • The successful candidate is expected to spend 50% of their time in Amsterdam and 50% of their time in Eindhoven.
  • After successful completion of the PhD research a PhD degree will be granted at a Dutch University.
  • 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.

More information?
For further information about the position, please contact :

Prof. Dr. Martin van Hecke
E-mail: M.v.Hecke@amolf.nl

Prof. Dr. Yoeri van de Burgt
E-mail: Y.B.v.d.Burgt@tue.nl

Application
You can respond to this vacancy online via the button below.

Please annex your:

  • Resume;
  • Motivation on why you want to join the group (max. 1 page).

It is important to us to know why you want to join our team. This means that we will only consider your application if it entails your motivation letter.

Applications will be evaluated on a rolling basis and as soon as an excellent match is made, the position will be filled.

Online screening may be part of the selection.

Diversity code
AMOLF is highly committed to an inclusive and diverse work environment: we want to develop talent and creativity by bringing together people from different backgrounds and cultures. We recruit and select on the basis of competencies and talents. We strongly encourage anyone with the right qualifications to apply for the vacancy, regardless of age, gender, origin, sexual orientation or physical ability.

AMOLF has won the NNV Diversity Award 2022, which is awarded every two years by the Netherlands Physical Society for demonstrating the most successful implementation of equality, diversity and inclusion (EDI).

Commercial activities in response to this ad are not appreciated.

17 sollicitaties
105 views


19-09-2025 AMOLF
PhD-student: Active Hysterons and Spiking Neurons for Physical Computing

Work Activities

We are seeking a motivated PhD- student to join our teams working on bistable elements for in-materia computing, as part of a joint theoretical/experimental program carried out at AMOLF (Amsterdam) and TU/e (Eindhoven).

Computing with artificial neurons takes inspiration from nature’s efficient, adaptive use of multistable networks, offering an alternative to energy-intensive digital systems with rigid bits and separated memory and computation. In this project, we aim to design and realize the first networks combining active and passive electronic neurons, using organic electronics for chemical and electrical tunability. This work is based on recent breakthroughs in our groups.
The Van Hecke group recently showed that passive, bistable hysterons excel at sequential tasks such as counting1,2, whereas the group of van de Burgt has built active electronic neurons that mimic spiking3,4. Surprisingly, we found that spiking neurons can be described as ‘active’ hysterons, forming a bridge between two distinct frameworks for in-materia computing. Hence, by combining active and passive elements we aim to combine the best of both worlds, endowing passive networks with adaptability and spiking networks with memory and sequencing. We will explore the computational power of these systems and demonstrate it in simple robots. Our work bridges organic neural systems and hysteron computing, and leverages (bio)chemical and electrical feedback to materialize adaptivity and plasticity.

Key questions include: How to realize and design mixed networks of passive and active artificial neurons? How do mixed networks extend the class of realizable computing? Do our networks exhibit spiking, bursting or synchronization, and how to control these behaviors? How to realize targeted sequential and adaptive computations? Can we develop neuronal circuits for maze-solving and sequential adaptation? To answer these questions, the project will involve computational modelling and experimental work, jointly supervised by Martin van Hecke and Yoeri van de Burgt. With this research, we aim to redefine physical computation.

To get an idea of our work, see:

[1] Kwakernaak and van Hecke, Counting and Sequential Information Processing in Mechanical Metamaterials, PRL 130 268204 (2023)

[2] Liu, Teunisse, Korovin, Vermaire, Jin, Bense and van Hecke, Controlled Pathways and Sequential Information Processing in Serially Coupled Mechanical Hysterons, PNAS 121, e2308414121 (2024).
[3] Matrone, van Doremaele, Surendran, Laswick, Griggs, Ye, McCulloch, Santoro, Rivnay and van de Burgt, A modular organic neuromorphic spiking circuit for retina-inspired sensory coding and neurotransmitter-mediated neural pathways, Nat Comm 15, 2868 (2024)

[4] Gkoupidenis, Zhang, Kleemann, Ling, Santoro, Fabiano, Salleo and van de Burgt, Organic mixed conductors for bioinspired electronics, Nat Rev Mat 9, 134 (2023)

[5] Baconnier, Teunisse and van Hecke, Dynamic self-loops in networks of passive and active binary elements, arXiv:2412.12658

Qualifications
We seek candidates with a strong background in physics, electrical\mechanical engineering, materials science, or computer science with an interest in complex materials for computing and learning. Excellent candidates with training in any area of science or engineering will be considered. PhD candidates must meet the requirements for an MSc degree. Good verbal and written communication skills in English are required. Other advantageous qualities include experience with coding (Python\Matlab) and numerical methods, as well as familiarity with concepts in complex systems, physical memories or machine learning. We strongly believe in the benefits of an inclusive and diverse research environment, and welcome applicants with any background.

Work environment
AMOLF is a part of NWO-I and initiate and performs leading fundamental research on the physics of complex forms of matter, and to create new functional materials, in partnership with academia and industry. The institute is located at Amsterdam Science Park and currently employs about 140 researchers and 80 support employees. www.amolf.nl

Working conditions

  • The working atmosphere at the institute is largely determined by young, enthusiastic, mostly foreign employees. Communication is informal and runs through short lines of communication.
  • 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
  • The starting salary is 2.968 Euro’s gross per month and a range of employment benefits.
  • The successful candidate is expected to spend 50% of their time in Amsterdam and 50% of their time in Eindhoven.
  • After successful completion of the PhD research a PhD degree will be granted at a Dutch University.
  • 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.

More information?
For further information about the position, please contact :

Prof. Dr. Martin van Hecke
E-mail: M.v.Hecke@amolf.nl

Prof. Dr. Yoeri van de Burgt
E-mail: Y.B.v.d.Burgt@tue.nl

Application
You can respond to this vacancy online via the button below.

Please annex your:

  • Resume;
  • Motivation on why you want to join the group (max. 1 page).

It is important to us to know why you want to join our team. This means that we will only consider your application if it entails your motivation letter.

Applications will be evaluated on a rolling basis and as soon as an excellent match is made, the position will be filled.

Online screening may be part of the selection.

Diversity code
AMOLF is highly committed to an inclusive and diverse work environment: we want to develop talent and creativity by bringing together people from different backgrounds and cultures. We recruit and select on the basis of competencies and talents. We strongly encourage anyone with the right qualifications to apply for the vacancy, regardless of age, gender, origin, sexual orientation or physical ability.

AMOLF has won the NNV Diversity Award 2022, which is awarded every two years by the Netherlands Physical Society for demonstrating the most successful implementation of equality, diversity and inclusion (EDI).

Commercial activities in response to this ad are not appreciated.

14 sollicitaties
0 views


19-09-2025 AMOLF
PhD-student: Self-Learning Metamaterials

Work Activities
We are seeking a motivated PhD student to join our team working on realizing learning in novel physical materials, as part of a joint theoretical/experimental research project between AMOLF and the University of Amsterdam (UvA).

Living systems capture our imagination in their incredible resilience and ability to adapt and prosper in the face of change in their environments. In comparison, human-made materials work reliably until an external change or internal aging cause them to fail once and for all. In this project, we will utilize a physical learning approach to imbue metamaterials and robots with intrinsic adaptation and learning from their experiences.

Using a combination of theory, numerical experiments and precision desktop experiments, we will create 3D materials with self-adapting elastic elements that counteract changes in the environment and the aging of their own parts. We will study how to make these materials learn continually by adapting functions over their lifetime without forgetting old lessons. Thereby, we will bring synthetic materials a large step closer to their living counterparts. With this project, we aim to redefine the way we engineer materials with direct ramifications in adaptive materials and robotics.

We offer a PhD position that combines theoretical exploration and experimental realization of a new class of robotic learning metamaterial, based on active and non-reciprocal elastic elements with controllable stiffness. The project will involve analytical and computational modelling, as well as designing and conducting lab experiments. Key questions include: How to create materials that can self-learn bulk visco-elastic properties? How to structure such materials to learn continually and counteract the aging of their own parts? Can we optimize self-learning materials to achieve properties that are hard to combine? With this research, we aim combine materials engineering with evolution and learning theory, blurring the lines between synthetic materials and adapting living systems.

For more information about our work, see:

[1] Jonas Veenstra, Colin Scheibner, Martin Brandenbourger, Jack Binysh, Anton Souslov, Vincenzo Vitelli, and Corentin Coulais. Adaptive locomotion of active solids. Nature, 639(8056):935–941 (2025).

[2] Yao Du, Jonas Veenstra, Ryan van Mastrigt, and Corentin Coulais. Metamaterials that learn to change shape. arXiv:2501.11958 (2025).

[3] Stern and Murugan, Learning without neurons in physical systems, Ann Rev Cond Matt Phys 14, 417 (2023)

[4] Dillavou, Beyer, Stern, Liu, Miskin and Durian, Machine learning without a processor: Emergent learning in a nonlinear analog network, PNAS 121, e2319718121 (2024)

Qualifications
We seek candidates with a strong background in physics, mechanical engineering, materials science, or computer science with an interest in complex meta-materials and (physical) learning. Excellent candidates with training in any area of science or engineering will be considered. PhD candidates must meet the requirements for an MSc degree. Good verbal and written communication skills in English are required. Other advantageous qualities include experience with coding (Python\Matlab) and numerical methods, as well as familiarity with concepts in complex systems, physical memories or machine learning. We strongly believe in the benefits of an inclusive and diverse research environment, and welcome applicants with any background.

Work environment
AMOLF is a part of NWO-I and initiate and performs leading fundamental research on the physics of complex forms of matter, and to create new functional materials, in partnership with academia and industry. The institute is located at Amsterdam Science Park and currently employs about 140 researchers and 80 support employees. www.amolf.nl

The Machine Materials laboratory at the University of Amsterdam is led by Corentin Coulais, with the goal of developing artificial materials which combine microstructure and out-of-equilibrium processes to interact with their environment in a programmable fashion.

The Learning Machines group is a new group at AMOLF, led by Menachem (Nachi) Stern, and focuses on the development of fundamental understanding and theories regarding learning, from a physical perspective, under real world constraints.

Our group members work closely together with extensive support from us and AMOLF resources in all aspects of design, realization, and interpretation of computational models of mechanical metamaterials and physical learning systems. We have a strong focus on stimulating development of students in all professional aspects, as well as collaborations with other researchers at our institutes and beyond. Moreover, we work closely together with international groups and companies.

Working conditions
The position is hosted at AMOLF, and the successful candidate will be enrolled for a Ph.D. program an the University of Amsterdam with joint supervision of Dr. Coulais and Dr. Stern. The experimental elements of the work will be carried at the science park campus of the University of Amsterdam.

  • The working atmosphere at AMOLF is largely determined by young, enthusiastic, mostly foreign employees. Communication is informal and runs through short lines of communication.
  • 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
  • The starting salary is 2.968 Euro’s gross per month and a range of employment benefits.
  • After successful completion of the PhD research a PhD degree will be granted at the University of Amsterdam.
  • 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.

More information?
For further information about the position, please contact:

Dr. Menachem Stern
E-mail: stern@amolf.nl

Dr. Corentin Coulais
E-mail: C.J.M.Coulais@uva.nl

Application
You can respond to this vacancy online via the button below.

Online screening may be part of the selection.

Diversity code
AMOLF is highly committed to an inclusive and diverse work environment: we want to develop talent and creativity by bringing together people from different backgrounds and cultures. We recruit and select on the basis of competencies and talents. We strongly encourage anyone with the right qualifications to apply for the vacancy, regardless of age, gender, origin, sexual orientation or physical ability.

AMOLF has won the NNV Diversity Award 2022, which is awarded every two years by the Netherlands Physical Society for demonstrating the most successful implementation of equality, diversity and inclusion (EDI).

Commercial activities in response to this ad are not appreciated.

30 sollicitaties
0 views


11-09-2025 AMOLF
PhD-student: Self-Learning Metamaterials

Work Activities
We are seeking a motivated PhD student to join our team working on realizing learning in novel physical materials, as part of a joint theoretical/experimental research project between AMOLF and the University of Amsterdam (UvA).

Living systems capture our imagination in their incredible resilience and ability to adapt and prosper in the face of change in their environments. In comparison, human-made materials work reliably until an external change or internal aging cause them to fail once and for all. In this project, we will utilize a physical learning approach to imbue metamaterials and robots with intrinsic adaptation and learning from their experiences.

Using a combination of theory, numerical experiments and precision desktop experiments, we will create 3D materials with self-adapting elastic elements that counteract changes in the environment and the aging of their own parts. We will study how to make these materials learn continually by adapting functions over their lifetime without forgetting old lessons. Thereby, we will bring synthetic materials a large step closer to their living counterparts. With this project, we aim to redefine the way we engineer materials with direct ramifications in adaptive materials and robotics.

We offer a PhD position that combines theoretical exploration and experimental realization of a new class of robotic learning metamaterial, based on active and non-reciprocal elastic elements with controllable stiffness. The project will involve analytical and computational modelling, as well as designing and conducting lab experiments. Key questions include: How to create materials that can self-learn bulk visco-elastic properties? How to structure such materials to learn continually and counteract the aging of their own parts? Can we optimize self-learning materials to achieve properties that are hard to combine? With this research, we aim combine materials engineering with evolution and learning theory, blurring the lines between synthetic materials and adapting living systems.

For more information about our work, see:

[1] Jonas Veenstra, Colin Scheibner, Martin Brandenbourger, Jack Binysh, Anton Souslov, Vincenzo Vitelli, and Corentin Coulais. Adaptive locomotion of active solids. Nature, 639(8056):935–941 (2025).

[2] Yao Du, Jonas Veenstra, Ryan van Mastrigt, and Corentin Coulais. Metamaterials that learn to change shape. arXiv:2501.11958 (2025).

[3] Stern and Murugan, Learning without neurons in physical systems, Ann Rev Cond Matt Phys 14, 417 (2023)

[4] Dillavou, Beyer, Stern, Liu, Miskin and Durian, Machine learning without a processor: Emergent learning in a nonlinear analog network, PNAS 121, e2319718121 (2024)

Qualifications
We seek candidates with a strong background in physics, mechanical engineering, materials science, or computer science with an interest in complex meta-materials and (physical) learning. Excellent candidates with training in any area of science or engineering will be considered. PhD candidates must meet the requirements for an MSc degree. Good verbal and written communication skills in English are required. Other advantageous qualities include experience with coding (Python\Matlab) and numerical methods, as well as familiarity with concepts in complex systems, physical memories or machine learning. We strongly believe in the benefits of an inclusive and diverse research environment, and welcome applicants with any background.

Work environment
AMOLF is a part of NWO-I and initiate and performs leading fundamental research on the physics of complex forms of matter, and to create new functional materials, in partnership with academia and industry. The institute is located at Amsterdam Science Park and currently employs about 140 researchers and 80 support employees. www.amolf.nl

The Machine Materials laboratory at the University of Amsterdam is led by Corentin Coulais, with the goal of developing artificial materials which combine microstructure and out-of-equilibrium processes to interact with their environment in a programmable fashion.

The Learning Machines group is a new group at AMOLF, led by Menachem (Nachi) Stern, and focuses on the development of fundamental understanding and theories regarding learning, from a physical perspective, under real world constraints.

Our group members work closely together with extensive support from us and AMOLF resources in all aspects of design, realization, and interpretation of computational models of mechanical metamaterials and physical learning systems. We have a strong focus on stimulating development of students in all professional aspects, as well as collaborations with other researchers at our institutes and beyond. Moreover, we work closely together with international groups and companies.

Working conditions
The position is hosted at AMOLF, and the successful candidate will be enrolled for a Ph.D. program an the University of Amsterdam with joint supervision of Dr. Coulais and Dr. Stern. The experimental elements of the work will be carried at the science park campus of the University of Amsterdam.

  • The working atmosphere at AMOLF is largely determined by young, enthusiastic, mostly foreign employees. Communication is informal and runs through short lines of communication.
  • 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
  • The starting salary is 2.968 Euro’s gross per month and a range of employment benefits.
  • After successful completion of the PhD research a PhD degree will be granted at the University of Amsterdam.
  • 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.

More information?
For further information about the position, please contact:

Dr. Menachem Stern
E-mail: stern@amolf.nl

Dr. Corentin Coulais
E-mail: C.J.M.Coulais@uva.nl

Application
You can respond to this vacancy online via the button below.

Online screening may be part of the selection.

Diversity code
AMOLF is highly committed to an inclusive and diverse work environment: we want to develop talent and creativity by bringing together people from different backgrounds and cultures. We recruit and select on the basis of competencies and talents. We strongly encourage anyone with the right qualifications to apply for the vacancy, regardless of age, gender, origin, sexual orientation or physical ability.

AMOLF has won the NNV Diversity Award 2022, which is awarded every two years by the Netherlands Physical Society for demonstrating the most successful implementation of equality, diversity and inclusion (EDI).

Commercial activities in response to this ad are not appreciated.

114 sollicitaties
290 views


11-09-2025 AMOLF
Strategic Lead Valorization (Interim Position / Freelance)

...

5 sollicitaties
0 views


28-08-2025 AMOLF