PhD-student: Physical Learning in Dynamical Systems

Work Activities
We are seeking a motivated PhD student to join our learning machines group at AMOLF and work on the theory of learning in dynamical physical systems, as part of an ERC Starting Grant project on Physical Learning in Dynamical Systems (PhyLDS).

Learning is often viewed as a computational process that takes place in brains or computers. Yet many physical systems, from biological networks to adaptive materials, continuously modify their behavior based on past experience. Despite the ubiquity of such adaptive phenomena, physics still lacks a general understanding of how learning emerges in dynamical systems that operate far from equilibrium.

In this project, we will develop a new theoretical framework for learning in physical systems with time-dependent dynamics. Unlike conventional machine learning algorithms, these systems learn through local interactions and physical feedback, without centralized optimization or backpropagation. We will investigate how learning is constrained by locality, causality, non-reciprocity, and dissipation, and how these constraints shape the ability of matter to learn.

The project combines analytical theory with large-scale numerical simulations. We will study diverse classes of adaptive dynamical networks, including flow networks, mechanical networks, and neuronal systems. A central goal is to identify the physical principles that govern learning in these systems, including scaling laws, phase diagrams, and fundamental limits.

The PhD student will contribute to:

• Developing local learning rules for dynamical physical systems;
• Comparing physical learning approaches to idealized gradient-based methods;
• Investigating when and why physical learning succeeds or fails;
• Exploring the role of feedback, non-equilibrium dynamics, and task complexity in learning;
• Developing efficient simulation tools for adaptive dynamical networks;
• Identifying scaling laws, phase boundaries, and universal features of learning in matter.

The project offers a unique opportunity to work at the intersection of condensed matter physics, non-equilibrium statistical mechanics, complex systems, machine learning, and biological physics. The successful candidate will help establish a new physics of adaptive matter and contribute to a growing international research effort aimed at understanding learning as a physical phenomenon.

For more information about our work, see:

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

[2] Stern, Hexner, Rocks and Liu, Supervised learning in physical networks: From machine learning to learning machines, Phys. Rev. X 11, 021045 (2021)

[3] Stern, Frim, Candás, Liu and Balasubramanian, Contrastive learning in tunable dynamical system, arXiv:2603.26969 (2026)

Qualifications
We seek candidates with a strong background in physics, mechanical engineering, materials science, or computer science with an interest in learning theory, broadly defined, condensed matter and complex systems. 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 dynamical 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 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 the group leader and AMOLF resources in all aspects of design, realization, and interpretation of computational models of 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 institute and beyond. Moreover, we work closely together with international groups and companies.

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 3.115 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 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:

Dr. Menachem Stern

E-mail: stern@amolf.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.

PhD-student: Physical Learning in Dynamical Systems

Work Activities
We are seeking a motivated PhD student to join our learning machines group at AMOLF and work on the theory of learning in dynamical physical systems, as part of an ERC Starting Grant project on Physical Learning in Dynamical Systems (PhyLDS).

Learning is often viewed as a computational process that takes place in brains or computers. Yet many physical systems, from biological networks to adaptive materials, continuously modify their behavior based on past experience. Despite the ubiquity of such adaptive phenomena, physics still lacks a general understanding of how learning emerges in dynamical systems that operate far from equilibrium.

In this project, we will develop a new theoretical framework for learning in physical systems with time-dependent dynamics. Unlike conventional machine learning algorithms, these systems learn through local interactions and physical feedback, without centralized optimization or backpropagation. We will investigate how learning is constrained by locality, causality, non-reciprocity, and dissipation, and how these constraints shape the ability of matter to learn.

The project combines analytical theory with large-scale numerical simulations. We will study diverse classes of adaptive dynamical networks, including flow networks, mechanical networks, and neuronal systems. A central goal is to identify the physical principles that govern learning in these systems, including scaling laws, phase diagrams, and fundamental limits.

The PhD student will contribute to:

• Developing local learning rules for dynamical physical systems;
• Comparing physical learning approaches to idealized gradient-based methods;
• Investigating when and why physical learning succeeds or fails;
• Exploring the role of feedback, non-equilibrium dynamics, and task complexity in learning;
• Developing efficient simulation tools for adaptive dynamical networks;
• Identifying scaling laws, phase boundaries, and universal features of learning in matter.

The project offers a unique opportunity to work at the intersection of condensed matter physics, non-equilibrium statistical mechanics, complex systems, machine learning, and biological physics. The successful candidate will help establish a new physics of adaptive matter and contribute to a growing international research effort aimed at understanding learning as a physical phenomenon.

For more information about our work, see:

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

[2] Stern, Hexner, Rocks and Liu, Supervised learning in physical networks: From machine learning to learning machines, Phys. Rev. X 11, 021045 (2021)

[3] Stern, Frim, Candás, Liu and Balasubramanian, Contrastive learning in tunable dynamical system, arXiv:2603.26969 (2026)

Qualifications
We seek candidates with a strong background in physics, mechanical engineering, materials science, or computer science with an interest in learning theory, broadly defined, condensed matter and complex systems. 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 dynamical 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 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 the group leader and AMOLF resources in all aspects of design, realization, and interpretation of computational models of 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 institute and beyond. Moreover, we work closely together with international groups and companies.

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 3.115 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 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:

Dr. Menachem Stern

E-mail: stern@amolf.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.

PhD- student: Harnessing phase transitions for optical information processing

Work Activities
This PhD project will investigate how phase transitions can be harnessed for information processing with light. Near a continuous phase transition, the susceptibility of a material can increase strongly. This allows weak input signals to generate large responses, which can in turn reduce the optical energy required for an operation. However, critical slowing down and enhanced fluctuations may limit processing speed and accuracy. The main objective of this PhD project is to quantify this trade-off between energy consumption, speed and accuracy in information processing near a phase transition, and to determine how it depends on properties of the signal such as amplitude and bandwidth.

The project builds on a recent work by the host group [Keijsers et al., Nature Photon. 19, 733 (2025)], where signatures of a phase transition were observed in the nonlinear response of a laser-driven optical cavity containing a perovskite crystal. The first objective is to characterize the spectral and temporal response of this system near the transition, which is expected to include memory effects and strong fluctuations. Next, controlled time-dependent signals and benchmark optical information-processing operations will be used to compare performance at different distances from the phase transition. Experiments will be combined with theoretical modelling, statistical data analysis, and numerical simulations to identify the governing mechanisms and to determine whether and how proximity to a phase transition offers an advantage for processing certain signals. The project is primarily experimental and will involve optical cavity measurements, materials characterization and, where needed, nanofabrication. Its expected outcome is an experimentally tested framework for designing photonic information-processing systems that exploit phase-transition physics.

Qualifications
You have an MSc degree in physics, optics, photonics, nanoscience, or a related field. Laboratory experience in optics or photonics is preferable but not strictly necessary. A background in, or strong interest in, one or more of the following areas is valued: nonlinear dynamics, condensed-matter physics, and stochastic processes. The ideal candidate is an experimentalist who enjoys not only setting up and performing complex experiments, but also thinking deeply about the results and modelling them. Applicants are not expected to bring expertise in all listed areas; the required methods will be learned during the project.

This is a collaborative project between AMOLF and Utrecht University. Your host will be the Interacting Photons group led by Prof. Said R. K. Rodriguez at AMOLF, but you will also work part time at Utrecht University with Prof. Allard Mosk and his group. We are therefore looking for someone who has the personal and communication skills required to connect two groups at different locations (half hour away), besides being able to work independently. The appointment also includes a contribution to teaching at Utrecht University and participation in the relevant training programs.

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

In the Interacting Photons group, we search for new physics emerging from photon interactions. As a testbed for new ideas, we use nonlinear nanophotonic resonators. We are driven by fundamental physics questions relevant to improve the energy efficiency, speed, and precision of optical technologies such as novel sensors and computers.

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 3.115 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 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 Said R.K. Rodriguez: s.rodriguez@amolf.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.

PhD- student: Harnessing phase transitions for optical information processing

Work Activities
This PhD project will investigate how phase transitions can be harnessed for information processing with light. Near a continuous phase transition, the susceptibility of a material can increase strongly. This allows weak input signals to generate large responses, which can in turn reduce the optical energy required for an operation. However, critical slowing down and enhanced fluctuations may limit processing speed and accuracy. The main objective of this PhD project is to quantify this trade-off between energy consumption, speed and accuracy in information processing near a phase transition, and to determine how it depends on properties of the signal such as amplitude and bandwidth.

The project builds on a recent work by the host group [Keijsers et al., Nature Photon. 19, 733 (2025)], where signatures of a phase transition were observed in the nonlinear response of a laser-driven optical cavity containing a perovskite crystal. The first objective is to characterize the spectral and temporal response of this system near the transition, which is expected to include memory effects and strong fluctuations. Next, controlled time-dependent signals and benchmark optical information-processing operations will be used to compare performance at different distances from the phase transition. Experiments will be combined with theoretical modelling, statistical data analysis, and numerical simulations to identify the governing mechanisms and to determine whether and how proximity to a phase transition offers an advantage for processing certain signals. The project is primarily experimental and will involve optical cavity measurements, materials characterization and, where needed, nanofabrication. Its expected outcome is an experimentally tested framework for designing photonic information-processing systems that exploit phase-transition physics.

Qualifications
You have an MSc degree in physics, optics, photonics, nanoscience, or a related field. Laboratory experience in optics or photonics is preferable but not strictly necessary. A background in, or strong interest in, one or more of the following areas is valued: nonlinear dynamics, condensed-matter physics, and stochastic processes. The ideal candidate is an experimentalist who enjoys not only setting up and performing complex experiments, but also thinking deeply about the results and modelling them. Applicants are not expected to bring expertise in all listed areas; the required methods will be learned during the project.

This is a collaborative project between AMOLF and Utrecht University. Your host will be the Interacting Photons group led by Prof. Said R. K. Rodriguez at AMOLF, but you will also work part time at Utrecht University with Prof. Allard Mosk and his group. We are therefore looking for someone who has the personal and communication skills required to connect two groups at different locations (half hour away), besides being able to work independently. The appointment also includes a contribution to teaching at Utrecht University and participation in the relevant training programs.

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

In the Interacting Photons group, we search for new physics emerging from photon interactions. As a testbed for new ideas, we use nonlinear nanophotonic resonators. We are driven by fundamental physics questions relevant to improve the energy efficiency, speed, and precision of optical technologies such as novel sensors and computers.

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 3.115 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 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 Said R.K. Rodriguez: s.rodriguez@amolf.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.

Senior Software Engineer

Work Activities
Als Senior Software Engineer bij AMOLF bouw je software voor unieke experimentele onderzoeksopstellingen. Je ontwikkelt bijvoorbeeld software die lasers en motoren aanstuurt, data uit camera’s en sensoren verzamelt en meetresultaten verwerkt en opslaat.

Je werkt nauw samen met onderzoekers van AMOLF en ARCNL. Zij weten wat ze willen onderzoeken; samen bepalen jullie hoe software kan helpen om dat experiment technisch mogelijk te maken.

Je ontwikkelt applicaties in C# voor de .NET-omgeving op Windows en werkt aan uiteenlopende toepassingen binnen de laboratoria van AMOLF en ARCNL.

Je houdt je onder andere bezig met:

• aansturing van lasers, motoren en andere laboratoriumapparatuur;
• uitlezen van camera’s, detectoren en sensoren;
• verwerking, visualisatie en opslag van meetdata;
• uitbreiding en verbetering van de bestaande softwarearchitectuur;
• testen en in bedrijf stellen van software op onderzoeksopstellingen;
• adviseren van onderzoekers over software en automatisering.

De applicaties maken gebruik van een gezamenlijke codebase die volledig in eigen beheer is. Waar mogelijk, wordt ook met de meest recente software versies gewerkt (C#, Visual Studio en andere ontwikkeltools). Je krijgt ruimte om nieuwe technieken, tools en standaarden voor te stellen en als ze passen, ook daadwerkelijk toe te passen.

Qualifications

• Minimaal HBO werk- en denkniveau op het gebied van Software Engineering;
• Ruime ervaring met C#/.NET en Visual Studio;
• Ervaring met het zelfstandig ontwerpen en ontwikkelen van applicaties;
• Interesse in hardware, elektronica en meet- en regeltechniek;
• Enige affiniteit met wiskunde en natuurkunde om technische en experimentele vraagstukken te kunnen volgen.

Ervaring met Python, hardware-integratie of het aansturen van meetapparatuur is een pré.
De voertaal binnen de afdeling Software Engineering is Nederlands, de voertaal met de wetenschappers soms Nederlands en vaak Engels.

Work environment
Binnen AMOLF en ARCNL zijn circa 100 experimentele onderzoeksopstellingen in gebruik. De software die jij ontwikkelt wordt rechtstreeks gekoppeld aan apparatuur in het lab. Dat kan de ene keer gaan om nauwkeurige positioneringen en de andere keer om het verzamelen van meetdata uit een detector of camera. Je ziet daardoor heel concreet wat jouw software doet en waarvoor deze wordt gebruikt.

Je werkt daarbij veel samen met elektronica engineers, mechanici en wetenschappers. Daardoor krijg je vanzelf ook mee wat er naast de software gebeurt en hoe de verschillende onderdelen in een opstelling samenkomen.

Deze functie past daarom goed bij iemand die niet alleen graag programmeert, maar ook nieuwsgierig is naar de techniek eromheen en wil begrijpen wat er in het lab daadwerkelijk gebeurt.

AMOLF en ARCNL zijn gevestigd op het Amsterdam Science Park. Samen vormen zij een internationale werkomgeving met circa 240 onderzoekers en 80 ondersteunende medewerkers uit verschillende landen en culturen.

AMOLF verricht fundamenteel onderzoek naar nieuwe materialen en fysische verschijnselen. ARCNL richt zich op onderzoek naar de fysica en technologie achter nanolithografie en is een publiek-private samenwerking tussen ASML en meerdere Nederlandse kennisinstellingen.

De afdeling Software Engineering ondersteunt beide onderzoeksinstituten. Als Software Engineer werk je in een relatief jong en enthousiast team van zes collega’s. Je werkt dicht op de onderzoekers en laboratoria waarvoor je software ontwikkelt. De lijnen zijn kort en je ziet daardoor snel hoe jouw werk in de praktijk wordt gebruikt binnen een experiment.

Naast het dagelijkse werk worden er regelmatig activiteiten georganiseerd, zowel binnen als buiten het werk. Ook de personeelsvereniging van AMOLF organiseert gedurende het jaar verschillende activiteiten. Uiteraard bepaal je zelf waar je wel of niet bij aansluit.

Working conditions

• Salaris in schaal 8 of 9 (CAO Onderzoeksinstellingen) tot maximaal € 5.241 bruto per maand;
• 8% vakantiegeld;
• 8,33% eindejaarsuitkering;
• 42 vakantiedagen bij een fulltime dienstverband;
• Een werkweek van 32–40 uur;
• Tweejarig contract met intentie tot vast;
• Ruime opleidings- en ontwikkelmogelijkheden;
• Mogelijkheid om in overleg deels thuis te werken;
• Een vaste werkplek op het Amsterdam Science Park.

More information?
De selectieprocedure wordt verzorgd door het recruitmentbureau INTRIQ. Voor meer informatie kun je contact opnemen met Sven Karass via 06 820 93 228 of sven@intriq.nl.

Application
Voor deze functie bieden wij geen sponsoring voor een verblijfs- of werkvergunning.

Je kunt je interesse kenbaar maken door te solliciteren via de website van het recruitmentbureau INTRIQ. Klik op de onderstaande link om te solliciteren:

Vacature - Senior Software Engineer - Amsterdam Science Park | INTRIQ | Technisch Recruitment

Diversity code
AMOLF and ARCNL are 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.

Commercial activities in response to this ad are not appreciated.