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

Introduction
This PhD project, part of the REACT MSCA Doctoral Network, aims to develop an energy-efficient compute-in-memory (CIM) architecture using gain-cell memory for real-time edge learning, addressing power, latency, and memory bandwidth issues with reliable fault detection.

Job Description
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.

Job Requirements

• You may not have resided or carried out your main activity in The Netherlands for more than 12 months in the 3 years immediately before the recruitment date.
• You may not already possess a doctoral degree at the date of recruitment.
• You must have Master degree or equivalent in Electrical Engineering with excellent grades.
• You should have knowledge of Digital/Mixed-Signal Integrated Circuit (IC) design and Computer Architecture.
• You should have solid skills in HDL (Verilog, VHDL) and scripting languages (Python, TCL).
• You should have experience with commercial EDA tools (Cadence/Mentor Graphics).
• Knowledge in Neuromorphic architectures and Low power IC design would be a definite plus.
• We are looking for a candidate with a research-oriented attitude, who is capable of taking initiatives, and has a strong problem-solving attitude.
• You should be able to work in an interdisciplinary team.
• Motivated to develop your teaching skills and coach students.
• 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 mission of the Department of Electrical Engineering is to acquire, share and transfer knowledge and understanding in the whole field of Electrical Engineering through education, research and valorization. We work towards a ‘Smart Sustainable Society’, a ‘Connected World’, and a healthy humanity (‘Care & Cure’). Activities share an application-oriented character, a high degree of complexity and a large synergy between multiple facets of the field.

Research is carried out into the applications of electromagnetic phenomena in all forms of energy conversion, telecommunication and electrical signal processing. Existing and new electrical components and systems are analyzed, designed and built. The Electrical Engineering department takes its inspiration from contacts with high-tech industry in the direct surrounding region and beyond.

The department is innovative and has international ambitions and partnerships. The result is a challenging and inspiring setting in which socially relevant issues are addressed.

Information
Do you recognize yourself in this profile and would you like to know more? Please contact the hiring manager Dr. Manil Dev Gomony, m.gomony@tue.nl.

Visit our website for more information about the application process. You can also contact Kevin Caris, HR Advisor, k.t.caris@tue.nl or +31 40 2478835.

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 and concurrently at the application portal in the project website https://project-react.eu/vacancies/. The application should include a:

• A clearly written cover letter (maximum one page) explaining your motivation for applying.
• A detailed curriculum vitae (CV) in English, including a list of publications (if applicable).
• Copies of official BSc/MSc degree certificates and corresponding academic transcripts for each degree.

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.

PhD In Urbanism

Co-design and adoption of European digital twin infrastructure for living environments

Introduction
Are you passionate about participatory and critical approaches to the design of digital infrastructures in cities? Do questions about fairness, legitimacy, and responsible AI in healthy urban living environments inspire you? In this PhD position, you will join a large international European consortium developing digital twin infrastructures across multiple countries. You will work alongside researchers, developers, healthcare actors, and housing/urban policy partners to strengthen the societal foundations of AI-enabled systems and contribute to a more just and inclusive digital transformation of living environments.

Job Description
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.

Job Requirements

• A master’s degree (or an equivalent university degree) in urbanism, urban studies, geography, planning, information systems, or a related field
• Demonstrated experience with participatory design, stakeholder engagement, or co-design processes
• Familiarity with urban data systems, and AI-enabled information models
• Basic experience with computational tools for data or text analysis (e.g. Python) and interest in AI-supported methods such as large language models in research contexts
• Interest in the governance, adoption, and societal implications of AI-enabled infrastructures
• Ability to easily switch between disciplinary frames and work across academic and societal contexts
• A research-oriented attitude and motivation to develop scientific work
• A critical attitude toward AI-enabled technologies and their application to building and spatial issues.
• Fluent in spoken and written English (C1 level). Knowledge of Dutch, Finish, or Greek is a plus.

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.

Sustainability, in its broadest definition, is the cornerstone of research and education in the Department of Built Environment. We take the lead in (re)shaping the built environment to be future-proof, safe, healthy, inclusive and respectful of planetary boundaries. We house the entire spectrum of technology, engineering, design, and human behavior disciplines in the built environment, with world-class experimental facilities at all scales. This allows us to address societal challenges from a uniquely integrated perspective.

Information
Do you recognize yourself in this profile and would you like to know more? Please contact the hiring manager Oana Druta (o.druta@tue.nl) or Cem Ataman (c.ataman@tue.nl).

Visit our website for more information about the application process. You can also contact Leo van Houten (HR Advisor) – (l.v.houten@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. No more than 2 A4 pages.
• Curriculum vitae, including a list of your publications (if applicable) and the contact information of two 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. Please note that incomplete applications may not be considered and could be rejected.

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.

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.