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.

Postdoc position: Controlling splashing and debris from solidifying tin droplets

Work Activities
This experiment-oriented postdoctoral position lies at the interface of fluid mechanics, phase-change physics, and industrial application. It is part of ARCNL’s Source Department and the EUV Plasma Processes group. We investigate the fundamental dynamics of liquid-tin targets and plasmas that underpin present and future extreme-ultraviolet (EUV) light sources for nanolithography. This project is carried out in close collaboration with industry.

Our group combines precision experiments, advanced imaging, and modeling to uncover the physics of tin droplets under extreme conditions of laser irradiation. We have established a strong track record in laser-droplet interaction, droplet deformation, and fragmentation physics. Our recently published works include laser-driven sheet formation and propulsion, curvature inversion in thin films, transitions between droplet oscillation and breakup, and singular jetting in free-falling droplets [e.g. J. Fluid Mech. 1020, A21 (2025); J. Fluid Mech. 1034, A26 (2026); Phys. Rev. Fluids 11, 073602 (2026)].

This project builds directly on that expertise to uncover how rapid solidification governs splashing, adhesion, and debris formation when molten-tin droplets impact solid substrates.

Background
Molten droplets impacting colder surfaces are encountered in applications ranging from EUV lithography to metal additive manufacturing and droplet-based printing. During impact, inertial spreading, capillary retraction, heat transfer, and solidification can occur on comparable timescales. Depending on impact conditions and surface properties, the droplet may adhere, rebound, splash, freeze, peel from the surface after solidification, or break up into smaller secondary droplets.

Although droplet splashing and solidification during impact have each received substantial attention, their strongly coupled dynamics under reduced ambient pressure remain insufficiently understood. Establishing which physical mechanisms, dimensionless parameters, and scaling laws remain valid across these scales is therefore both a fundamental and technologically relevant problem.

Project goal
The project aims to develop a predictive, experimentally grounded understanding of how rapid solidification and ambient pressure shape molten-tin droplet impacts, and to use this insight to identify surfaces and operating conditions that minimize splashing and debris formation. You will start from a droplet-on-demand platform for millimeter-sized molten-tin droplets, with systematic control over ambient pressure, substrate temperature, impact velocity, and surface properties, combined with synchronized high-speed side- and bottom-view imaging.

You will establish quantitative regime maps for spreading, sticking, rebound, freezing, peeling, and fragmentation. Using existing image-analysis tools and newly developed workflows, you will quantify droplet deformation, contact-line motion, solidification dynamics, and the size and velocity distributions of secondary droplets. These measurements will form the basis for predictive scaling relations that describe fragment formation across pressure and temperature conditions.

Together with collaborators at TU/e and UvA, and through interaction with industrial partners, you will translate the resulting physical understanding into practical design principles for low-debris surfaces and operating windows in advanced EUV source environments.

Qualifications

• You have (or will soon obtain) a PhD in (Applied) Physics, Mechanical Engineering, Chemical Engineering, Materials Science, or a closely related field.
• You have a strong experimental background and enjoy designing, building, and improving laboratory experiments.
• Experience in one or more of the following areas is an asset: fluid dynamics, droplet impact, multiphase flow, heat transfer, phase change, high-speed imaging, vacuum systems, optical diagnostics, or surface science.
• Experience with scientific programming and quantitative data analysis, particularly in Python, is welcomed.
• Experience with droplet generation, thermal diagnostics, image processing, or automated experimental control would be advantageous, but is not required.
• Strong verbal and written communication skills in English are required, together with enthusiasm for collaborative, hands-on research.
• You are motivated to take scientific ownership of the project, from experimental design and quantitative analysis to physical interpretation and publication.

Work environment
The Advanced Research Center for Nanolithography (ARCNL) focuses on the fundamental physics and chemistry involved in current and future key technologies in nanolithography, primarily for the semiconductor industry. ARCNL is a public-private partnership between the Dutch Research Council (NWO), the University of Amsterdam (UvA), Vrije Universiteit Amsterdam (VU), the University of Groningen (UG), and the semiconductor equipment manufacturer ASML. ARCNL is located at Amsterdam Science Park in the Netherlands and has approximately 100 scientists of which 65 are ambitious (young) researchers from all over the globe and support staff. See also www.arcnl.nl

Working conditions
The position is intended as full-time (40 hrs / week, 12 months / year) appointment in the service of the Netherlands Foundation for Scientific Research Institutes (NWO-I) for the duration of 2 years, with a starting salary of €4,552 gross per month, scale 10 (CAO-OI), and a range of employment benefits. A favorable tax agreement, the ‘30% ruling’, may apply to non-Dutch applicants. ARCNL assists any new foreign researchers with housing, subject to availability, and visa applications and compensates their transport costs and furnishing expenses.

Other conditions offered by ARCNL:

• Responsibility for a dedicated molten-tin droplet-impact setup with controlled ambient pressure and substrate temperature.
• The opportunity to obtain publishable results on a millimeter-scale droplet-on-demand platform whose design is workshop-ready.
• Hands-on work with high-speed imaging, vacuum technology, precision diagnostics, and surface-controlled impact experiments.
• A central role in designing and executing experimental campaigns and in developing quantitative fate maps for bouncing, sticking, peeling, and fragmentation.
• Rich image and time-resolved data sets, with scope to develop advanced analysis workflows in Python.
• Close scientific collaboration with researchers in fluid mechanics, theory, and numerical simulation at ARCNL, TU/e, and UvA.
• Possibility to enhance your experimental research work with advanced numerical simulations of complex fluid flows.
• Direct interaction with industrial partners and the opportunity to translate fundamental physics into contamination-mitigation strategies.
• A highly interdisciplinary environment spanning multiphase flow, laser-matter interaction, plasma physics, surface science, and nanolithography.

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

Dr. Oscar Versolato
Group leader EUV Plasma Processes
E-mail: versolato@arcnl.nl
Phone: +31 (0)20-851 7100

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

Please send your:

• Resume
• Motivation letter on why you want to join the group and this project (max. 1 page).

Online screening may be part of the selection.

Diversity code
ARCNL 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.

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: Physics-Informed Machine Learning for Semiconductor Metrology

Work Activities
How can we combine machine learning and physics to recover nanoscale information from imperfect images?
Modern computer chips are built with features only a few nanometers across, yet manufacturers need to measure these structures with extraordinary precision and do so quickly enough to keep up with large-scale production. This creates a fascinating computational challenge: how can we infer hidden physical properties from limited, noisy, and low-resolution measurement data?

In this project, you will develop a novel physics-informed machine learning approach that integrates physical simulations of the measurement process with its inverse reconstruction. A key challenge is the data-driven design of the experimental setup: exploring how the choice of measurements and configurations can be optimized to extract the most useful information for reliable parameter reconstruction.

You will work in close collaboration with the research department at ASML, the Centrum Wiskunde & Informatica (CWI, Prof. dr. Tristan van Leeuwen), and the AI4Science Lab, Informatics Institute, University of Amsterdam (dr. Patrick Forré), combining industrial relevance with academic depth in computational science and mathematical modeling.

Qualifications
You have (or soon will have) a MSc degree in computer science, machine learning, artificial intelligence, applied mathematics, physics, or a related discipline, meeting the Dutch university requirements for entry into a PhD program. A background in machine learning, inverse problems, scientific computing, or related data-driven methods is highly desirable. You are curious about combining physical modeling with data-driven methods and are motivated to work at the interface of academia and industry. Strong analytical skills, a collaborative mindset, and proficiency in verbal and written English are essential.

Work environment
ARCNL performs fundamental research, focusing on the physics and chemistry involved in current and future key technologies in nanolithography, primarily for the semiconductor industry. While the academic setting and research style are geared towards establishing scientific excellence, the topics in ARCNL’s research program are intimately connected with the interests of the industrial partner ASML. The institute is located at Amsterdam Science Park and currently employs about 100 persons of which 65 are ambitious (young) researchers from all over the globe. www.arcnl.nl

Working conditions
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 € 3.115 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. ARCNL 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 Lyuba Amitonova: l.amitonova@arcnl.nl and Maximilian Lipp (m.lipp@arcnl.nl).

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

Online screening may be part of the selection.

Diversity code
ARCNL 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.

Commercial activities in response to this ad are not appreciated.

Postdoc : Generating extreme ultraviolet light from plasma with a 2µm laser

Work Activities
This experiment-oriented postdoctoral position lies at the interface between fundamental physics and industrial application. It is part of activities in ARCNL’s Source Department. The research activities of the Source Department and its EUV Plasma Processes group aim at the atomic- and molecular-level understanding of the fundamental dynamics in the operation of contemporary and future plasma-based sources of extreme-ultraviolet (EUV) light for nanolithography.

In our group’s research we, for example, uncovered the quantum origins of the generated EUV light [Torretti, Nature Comms. Nature Commun. 11, (2020)], found a universal law for expanding plasma [Sheil, Phys. Rev. Lett. 133, (2024)], and found that less than half the initial droplet volume is present on thin tin sheet targets as used in EUV sources [Liu, Phys. Rev. Appl. 20, (2023)], and work on an alternative EUV source solution [Mostafa, Appl. Phys. Lett. 123, (2023)] – a concept that is most relevant for the current vacancy.

Background
The revolutionary introduction of EUV lithography was the culmination of several decades of collaborative work between industry and science – a Project Apollo of the digital age. The short, 13.5-nm EUV wavelength enables patterning the smallest, smartest, and most energy-efficient features on chips. The required 13.5-nm radiation is generated from plasma that is produced from tiny tin droplets that are heated by powerful laser pulses. At ARCNL, we are now thinking about the next generation of light sources: Can we make more energy efficient and more powerful EUV light sources?

Project goal
To identify what light source will power the next generation of lithography machines, we need to understand what plasma conditions are optimal for producing light from plasma, but also we need to understand how such plasma should be generated, and what laser technology should be used. You will join an interdisciplinary team of several PhD students and postdocs in ARCNL’s highly cohesive Source Department and have as an objective to design & execute experiments, and work with advanced laser technologies, to understand the emission of light and ions from plasma that you generate.

Qualifications

• You have (or will soon obtain) a PhD in (Applied) Physics.
• Knowledge of experimental laser and/or plasma physics is an asset, especially if combined with strong hands-on laboratory skills.
• Programming experience, particularly in Python, is welcomed.
• Strong verbal and written communication skills in English are required.

Work environment
The Advanced Research Center for Nanolithography (ARCNL) focuses on the fundamental physics and chemistry involved in current and future key technologies in nanolithography, primarily for the semiconductor industry. ARCNL is a public-private partnership between the Dutch Research Council (NWO), the University of Amsterdam (UvA), the VU University Amsterdam (VU), the University of Groningen (UG), and the semiconductor equipment manufacturer ASML. ARCNL is located at the Amsterdam Science Park, The Netherlands, and has a size of approximately 100 scientists and support staff. See also www.arcnl.nl

Working conditions
The position is intended as full-time (40 hrs / week, 12 months / year) appointment in the service of the Netherlands Foundation for Scientific Research Institutes (NWO-I) for the duration of up to 3 years, with a starting salary of €4,552 gross per month, scale 10 (CAO-OI), and a range of employment benefits. A favorable tax agreement, the ‘30% ruling’, may apply to non-Dutch applicants. ARCNL assists any new foreign researchers with housing, subject to availability, and visa applications and compensates their transport costs and furnishing expenses.

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

Dr. Oscar Versolato
Group leader EUV Plasma Processes
E-mail: versolato@arcnl.nl
Phone: +31 (0)20-851 7100

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

Please send your:

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

Online screening may be part of the selection.

Diversity code
ARCNL 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.

Commercial activities in response to this ad are not appreciated.