PhD on Emulation framework for self-aware neuromorphic system-on-chip architectures

As part of the REACT Marie Skłodowska-Curie Actions (MSCA) Doctoral Network initiative, we are seeking a highly motivated PhD candidate to join our research group working on next-generation neuromorphic computing systems. Inspired by the computational principles of the human brain, neuromorphic systems promise ultra-low-power intelligent processing through event-driven computation, on-chip learning, and compute-in-memory (CiM) paradigms that significantly reduce data movement between memory and processing units. However, evaluating such architectures at system scale remains a major challenge due to the limitations of conventional software simulation and existing device-level emulation platforms.

This PhD project will develop an advanced emulation framework, potentially FPGA-accelerated, for self-aware neuromorphic system-on-chip (SoC) architectures, enabling fast and accurate exploration of emerging hardware and learning paradigms. The framework will support rapid prototyping, automated design-space exploration, and cross-technology benchmarking, providing new insights into the co-design of learning algorithms, memory technologies, and neuromorphic hardware architectures for future edge-intelligent systems. Particular emphasis will be placed on energy-efficient CiM-based architectures, adaptive processing mechanisms, and secure AI acceleration for next-generation embedded and edge platforms.

Research objectives:

• Develop FPGA-based emulation and prototyping frameworks to accelerate the design-space exploration of neuromorphic SoC architectures leveraging emerging compute-in-memory (CiM) paradigms.
• Design energy-efficient, adaptive, and scalable neuromorphic SoC architectures integrating CiM technologies.
• Investigate security mechanisms for neuromorphic and AI accelerators, including side-channel resistance and secure on-chip learning.
• Implement, validate, and benchmark architectures using simulation environments and hardware prototypes.
• Collaborate with interdisciplinary research teams spanning artificial intelligence, circuit design, computer architecture, and embedded systems engineering.

PhD In Urbanism

Digital twins and AI-enabled infrastructures are increasingly shaping European health and living environments. Yet their success depends not only on technical robustness, but also on social acceptability, trust, and adoption. How can co-design processes contribute to fair, legitimate, and transferable digital infrastructures across countries and domains?

In this PhD project, you will work within a large international European consortium, funded under the Horizon Europe project AiGENT – AI-enabled digital twin infrastructure for health and living environments. The consortium involve universities, research institutes, healthcare and built environment actors, and civil society organisations across multiple countries. Your research will focus on evaluating and structuring co-design processes in this setting, with particular attention to how participatory approaches influence legitimacy, stakeholder value, and adoption dynamics in different national contexts.

You will design and analyse evaluation workshops and cross-domain focus groups in three pilot countries, engaging researchers, construction industry, housing portfolio managers, policy actors and residents. You will investigate issues such as fairness, bias, access, and power relations in AI-enabled infrastructures. In addition, you will develop a structured evaluation framework and explore how co-design processes can be enhanced by AI-supported tools, for example by comparing alternative scenarios, surfacing hidden tensions, or structuring stakeholder input in a transparent and comparable way across domains.

The project is embedded in an interdisciplinary research environment at TU/e, where you will collaborate with experts in urbanism, digital systems, and governance. You will contribute to methodological innovation, scientific publications, and the development of a European playbook for responsible and scalable digital twin infrastructures.

Through your work, you will help strengthen the societal grounding of AI-driven infrastructures and contribute to the responsible digital transformation of health and living environments in Europe.

PhD in Physical control of a soft artificial heart

How can we harness embodied nonlinear mechanical and dynamical behaviour to effectively control a soft robotic heart? In this PhD, you will design effective (physical) control strategies that can harness the “embodied intelligence” present in soft robotic hearts currently under development in the Holland Hybrid Heart consortium. Current devices that we work on are driven by compressed fluid (air or liquid). Based on a simulation framework that is currently being developed, you will explore how fluidic circuits that include self-oscillatory dynamics can be harnessed to achieve a heartbeat, and how basic control strategies can be used to obtain a target physiological output in various settings.

This work builds on recent research from the group that includes the development of soft fluidic artificial ventricles/hearts (see article published in Science Advances), and fluidic circuits that self-oscillate (see articles published in Matter, Nature Communications and Science). The main goal of this PhD is to create an understanding on how such embodied behaviour can be integrated in control strategies, to e.g. reduce the need for sensory input and increase the reliability of the completely integrated system that will be eventually evaluated in animal experiments.

Your role: You will design and experimentally implement fluidic circuits that physically control the soft artificial heart, specifically circuits that create a heartbeat and that potentially implement self-regulating mechanism (such as the Frank Starling mechanism, or the baroreceptor reflex). Next, to control this dynamical system, you will determine optimal sensor placement, and implement a controller that regulates the power to the pump, to achieve target physiological performance in different circumstances. A model is currently under development to support this more experimentally targeted research. You will closely work with group and consortium members, including those that are developing soft artificial hearts and will perform first animal trials.

You will build and test physical systems by using rapid prototyping techniques, develop measurement and analysis tools, and use available simulations to guide design and interpretation. This is both a curiosity-driven project as well as an application-oriented project, at the intersection of physics, soft robotics, nonlinear dynamics, and control, with the goal of redefining how we physically control machines. Your work will help establish new design principles for soft medical devices and robotic systems in general, that can operate robustly in uncertain environments without complex control.

Research environment: You will work in Autonomous Matter & Machines Lab at TU/e (formerly Soft Robotic Matter at AMOLF), which is part of the Dynamics & Control Section in the Mechanical Engineering Department. You will be embedded in a collaborative and inclusive team that combines experimental physics, materials science, and robotics, with access to state-of-the-art fabrication and experimental facilities.

The Autonomous Matter & Machines Lab explores how to embody autonomous behaviour in soft machines and materials. We draw inspiration from seemingly simple mechanical and dynamical phenomena like the sputtering of a ketchup bottle, the flailing of a sky dancer, or the symmetry-breaking occurring upon the inflation of interconnected balloons, that turn out to originate from rich nonlinear behaviour. These tangible and often playful systems provide deep insights into mechanics and dynamics, while also offering a unique entry point for knowledge sharing in research and beyond.

Our aim is to leverage these fundamental insights directly into real-world applications. Similar to how autonomy can emerge in natural systems, we demonstrate the opportunity for finding embodied alternatives to centralised processes (such as AI) that originate from dynamic interaction and environmental feedback. Applications that we are working on in collaboration with various partners include the development of a soft robotic heart that can autonomously adapt to physiological changes, soft grippers that can sense and handle delicate fruits and vegetables, and sustainable architectural facades that adapt to environmental conditions without external power or control.

PhD in Physical control of a soft artificial heart

Introduction
Are you fascinated by nonlinear mechanical and dynamical behaviour? Do you want to explore how we can use effects such as self-oscillations, mechanical adaptation and self-regulation to introduce and design emergent autonomous behaviour in soft machines? Do you want to directly apply these fundamental insights to control a soft artificial heart? Do you operate best in an interdisciplinary team?

Job Description
How can we harness embodied nonlinear mechanical and dynamical behaviour to effectively control a soft robotic heart? In this PhD, you will design effective (physical) control strategies that can harness the “embodied intelligence” present in soft robotic hearts currently under development in the Holland Hybrid Heart consortium. Current devices that we work on are driven by compressed fluid (air or liquid). Based on a simulation framework that is currently being developed, you will explore how fluidic circuits that include self-oscillatory dynamics can be harnessed to achieve a heartbeat, and how basic control strategies can be used to obtain a target physiological output in various settings.

This work builds on recent research from the group that includes the development of soft fluidic artificial ventricles/hearts (see article published in Science Advances), and fluidic circuits that self-oscillate (see articles published in Matter, Nature Communications and Science). The main goal of this PhD is to create an understanding on how such embodied behaviour can be integrated in control strategies, to e.g. reduce the need for sensory input and increase the reliability of the completely integrated system that will be eventually evaluated in animal experiments.

Your role: You will design and experimentally implement fluidic circuits that physically control the soft artificial heart, specifically circuits that create a heartbeat and that potentially implement self-regulating mechanism (such as the Frank Starling mechanism, or the baroreceptor reflex). Next, to control this dynamical system, you will determine optimal sensor placement, and implement a controller that regulates the power to the pump, to achieve target physiological performance in different circumstances. A model is currently under development to support this more experimentally targeted research. You will closely work with group and consortium members, including those that are developing soft artificial hearts and will perform first animal trials.

You will build and test physical systems by using rapid prototyping techniques, develop measurement and analysis tools, and use available simulations to guide design and interpretation. This is both a curiosity-driven project as well as an application-oriented project, at the intersection of physics, soft robotics, nonlinear dynamics, and control, with the goal of redefining how we physically control machines. Your work will help establish new design principles for soft medical devices and robotic systems in general, that can operate robustly in uncertain environments without complex control.

Research environment: You will work in Autonomous Matter & Machines Lab at TU/e (formerly Soft Robotic Matter at AMOLF), which is part of the Dynamics & Control Section in the Mechanical Engineering Department. You will be embedded in a collaborative and inclusive team that combines experimental physics, materials science, and robotics, with access to state-of-the-art fabrication and experimental facilities.

The Autonomous Matter & Machines Lab explores how to embody autonomous behaviour in soft machines and materials. We draw inspiration from seemingly simple mechanical and dynamical phenomena like the sputtering of a ketchup bottle, the flailing of a sky dancer, or the symmetry-breaking occurring upon the inflation of interconnected balloons, that turn out to originate from rich nonlinear behaviour. These tangible and often playful systems provide deep insights into mechanics and dynamics, while also offering a unique entry point for knowledge sharing in research and beyond.

Our aim is to leverage these fundamental insights directly into real-world applications. Similar to how autonomy can emerge in natural systems, we demonstrate the opportunity for finding embodied alternatives to centralised processes (such as AI) that originate from dynamic interaction and environmental feedback. Applications that we are working on in collaboration with various partners include the development of a soft robotic heart that can autonomously adapt to physiological changes, soft grippers that can sense and handle delicate fruits and vegetables, and sustainable architectural facades that adapt to environmental conditions without external power or control.

Job Requirements

• A master’s degree (or an equivalent university degree) in, e.g., Mechanical Engineering, Physics, Robotics.
• A research-oriented attitude.
• Ability to work in an interdisciplinary team and interested in public outreach activities.
• Motivated to develop your teaching skills and coach students.
• Hands-on experimental mindset (with rapid prototyping techniques), and affinity with data analysis.
• Analytical and problem-solving skills
• Initiative and creativity in developing new research direction
• Ability to collaborate in an interdisciplinary and inclusive environment
• Fluent in spoken and written English (C1 level).

Conditions of Employment
A meaningful job in a dynamic and ambitious university, in an interdisciplinary setting and within an international network. You will work on a beautiful, green campus within walking distance of the central train station. In addition, we offer you:

• Full-time employment for four years, with an intermediate assessment after nine months. You will spend a minimum of 10% of your four-year employment on teaching tasks, with a maximum of 15% per year of your employment.
• Salary and benefits (such as a pension scheme, paid pregnancy and maternity leave, partially paid parental leave) in accordance with the Collective Labour Agreement for Dutch Universities, scale P (min. € 3,059 - max. € 3,881).
• A year-end bonus of 8.3% and annual vacation pay of 8%.
• High-quality training programs and other support to grow into a self-aware, autonomous scientific researcher. At TU/e we challenge you to take charge of your own learning process.
• An excellent technical infrastructure, on-campus children's day care and sports facilities.
• Unlimited access to the modern on‑campus TU/e Student Sports Center at an exceptionally affordable rate.
• An allowance for commuting, working from home and internet costs.
• A Staff Immigration Team and a tax compensation scheme (the 30% facility) for international candidates.

On our website you can discover even more information about our conditions of employment. Build on your career at TU/e!

About us
We are a leading international university where scientific curiosity meets a hands-on mindset. We work in an open and collaborative way with high-tech industries to tackle complex societal challenges. Our responsible and respectful approach ensures impact — today and in the future. TU/e is home to over 13,000 students and more than 7,000 staff, forming a diverse and vibrant academic community.

Our university is located in Brainport Eindhoven — a world‑leading tech region with more than 7,000 high‑tech companies and strong R&D activity. Known for breakthroughs in AI, photonics, semiconductors and advanced manufacturing, Brainport is a place where technology serves people and society. Learn more about the Brainport region here.

The Department of Mechanical Engineering department conducts world-class research aligned with the technological interests of the high-tech industry in the Netherlands, with a focus on the Brainport region. Our goal is to produce engineers who are both scientifically educated and application-driven by providing a balanced education and research program that combines fundamental and application aspects. We equip our graduates with practical and theoretical expertise, preparing them optimally for future challenges.

Information
Do you recognize yourself in this profile and would you like to know more? Please contact the hiring manager Bas Overvelde (j.t.b.overvelde@tue.nl).

Visit our website for more information about the application process. You can also contact HRServices.me@tue.nl.

Curious to hear more about what it’s like as a PhD candidate at TU/e? Please view the video.

Are you inspired and would like to know more about working at TU/e? Please visit our career page.

Application
We invite you to submit a complete application by using the apply button. The application should include a:

• Cover letter in which you describe your motivation and qualifications for the position.
• Curriculum vitae, including a list of your publications and the contact information of three references. Kindly note that we may reach out to references at any stage of the recruitment process. We recommend notifying your references upon submitting your application.

Ensure that you submit all the requested application documents. We give priority to complete applications.

We look forward to receiving your application and will screen it as soon as possible. The vacancy will remain open until the position is filled.

Please note

• You can apply online. We will not process applications sent by email and/or post.
• A pre-employment screening (e.g. knowledge security check) can be part of the selection procedure. For more information on the knowledge security check, please consult the National Knowledge Security Guidelines.
• Please do not contact us for unsolicited services.

Postdoc in Integrated Single-Photon Avalanche Diode Array for Quantum Computing

We are looking for a skilled and motivated postdoc researcher who wants to develop high-performance components for a rapidly emerging application domain: photonic quantum computing. The candidate should also be motivated to dive into technological research to develop highly manufacturable heterogeneous integration process to transfer large arrays of SPADs onto SiN wafers, either through wafer bonding or micro-transfer printing.

The main task of the postdoc will be to design, fabricate and validate high efficiency SPADs based on InP photonic technology. The postdoc will need to address not only the fundamental quantum efficiency of the SPAD device itself, but also the interface between the SPAD and the SiN waveguide circuits. Therefore we are looking for a postdoc who can manage a relatively complex design and technology optimization problem. Besides, the postdoc will work closely with mission partners such as Quix Quantum as well as other sister projects within the mission. For instance, a joint development with an inverse design focused project is foreseen to realize ultralow loss III-V to SiN couplers.

You will work in the Photonic Integration group (PhI) which has about 80+ members. The technology development and device realization will be supported by experienced technicians in our cleanroom facilities at Nanolab@TU/e (www.tue.nl/nanolab). You will be embedded in a Quantum PIC topical team within PhI, formed by PhD and postdoc researchers from various related projects. Strong collaboration within the team is expected.