PhD in Organic Iontronic Neuromorphic Devices and Circuits

Introduction
Are you inspired by the challenge of building new technologies that connect materials, electronics and intelligent systems? Are you passionate about developing next-generation hardware for adaptive, efficient and intelligent technologies?

Job Description
Neuromorphic hardware promises efficient learning and control, yet nearly all existing platforms rely on rigid, silicon-based electronics and electron-only information carriers. In contrast, biological systems compute and control with hydrated ions, in soft and dynamic environments. Organic mixed ionic–electronic conductors (OMIECs) and iontronic circuits now offer an opportunity to move beyond electronics that imitate the brain towards soft, ion-based devices and circuit architectures that can be physically co-located with sensors, actuators and even biological tissues.

We will develop a fundamentally new class of organic iontronic neuromorphic devices and circuits such as memory elements and spiking neurons, and explore how they can implement learning control at the interface between the human body and intelligent robotic systems. The project builds on our previous work on organic electrochemical synapses, biohybrid synapses modulated by neurotransmitters, neuromorphic biosensors with on-chip learning and progressive hardware backpropagation in ECRAM arrays developed in our group (see: van de Burgt group which is part of the Microsystems Section). These achievements provide a unique platform to now ask deeper questions about control and computation with ions at the physical interface to the body.

The overall goal of this PhD project is:
To develop organic iontronic neuromorphic devices and circuits for smart adaptive biosensors and control

Embedding
The PhD student will be directly supervised by prof. Yoeri van de Burgt, Professor in Neuromorphic Engineering, within the Microsystems section, headed by prof. Jaap den Toonder. Microsystems is part of the Institute for Complex Molecular Systems (ICMS). The Microsystems section manages the Microfab lab, a state-of-the-art micro fabrication facility that houses a range of micro-manufacturing technologies.

Job Requirements
We are looking for a candidate with a background in electrical or circuit engineering, materials science, robotics, artificial intelligence, microsystems engineering, or another relevant discipline. Given the multidisciplinary character of the proposed research the ideal candidate has experience in device physics, circuits, sensors, microfabrication and materials science. Experience with control engineering is a plus. Furthermore, the candidate has a hands-on attitude, experimental experience and can work independently as well as collaborate with others.

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
prof.dr.ir. Yoeri van de Burgt (y.b.v.d.burgt@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.

Assistant-Associate Professor in Biomechanics of Regenerative Implants

Introduction

• Are you inspired by tissue and organ regeneration in the human body?
• Are you intrigued by engineering implants that induce and work synergistically with regenerating tissue to restore function?
• Are you fascinated by working at the cross-section of computational biomechanics, machine learning and data science?

Job Description
As an assistant/associate professor, you will establish a new research direction in the field of Regenerative Engineering & Materials (REM), with a strong emphasis on biomechanics of regenerative implants. Preference will be given to those focusing on hard tissues. Your research profile complements the existing areas of research within the REM cluster and the Department of Biomedical Engineering. This should include expertise in computational biomechanics and preferably experience/expertise in data-driven and hybrid modeling approaches. In addition to your own research, there are ample opportunities to collaborate on multidisciplinary research projects. You will take the lead in attracting funding for your research and will build connections and collaborations with researchers and research programs within the cluster, the department, TU/e, and internationally. You will develop, teach, and continuously improve courses for the BSc, MSc, and PhD educational programs in the Biomedical Engineering department, particularly in the area of biomechanics. You will supervise and mentor BSc, MSc, EngD, and PhD students, empowering the next generation of engineers, and you will conduct your research in our shared laboratories and computational facilities, where we collectively support one another in accessing advanced infrastructure.

Job Requirements

• An ambitious, collaborative, and passionate researcher and educator with a PhD in the field of biomedical engineering, mechanical engineering, or similar, with a keen interest in biomechanics and regenerative medicine.
• A distinguished record of academic achievements in research and education reflected in high-quality, impactful publications, research-based product ideas, patents, or other outputs.
• Ability to secure external research funding.
• An informed vision on teaching and learning within your own discipline. Affinity to contribute to the teaching program of the cluster. Demonstrated experience or assistance in teaching is an advantage.
• Strong cooperation skills and ability to work in an interdisciplinary team.
• Effective communication and leadership skills, including coaching and mentoring of students and staff, leading a project or chairing a group.
• Excellent (written and verbal) proficiency in English and preferably also in Dutch.
• We find it important that our staff reflects the 50% gender balance in our student population and therefore specifically invite female talent to apply.

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:

• A tailor-made career proposal (Assistant or Associate Professor) will be considered given your experience and track record.
• Salary in accordance with the Collective Labour Agreement for Dutch Universities, for a junior Assistant Professor this is (scale 11) min. €4,728 to max. €6,433 gross per month (on a full-time basis). For an Associate Professor the range of the gross salary is (scale 13/14) min. €6,512 to max. €8,673 gross per month (on a full-time basis).
• A year-end bonus of 8.3% and annual vacation pay of 8%.
• A dedicated mentoring program to help you get to know the university and the Dutch (research) environment.
• A Development Track with the prospect of becoming an Associate Professor. If you have a more senior profile, a tailor-made career proposal will be considered.
• High-quality training programs for academic leadership and teaching.
• 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.
• Partially paid parental leave and an allowance for commuting, working from home and internet costs.
• A Staff Immigration Team is available for international candidates, as are a tax compensation scheme (the 30% facility) and partner career support.

About us
Eindhoven University of Technology is an internationally top-ranking university in the Netherlands that combines scientific curiosity with a hands-on attitude. Our spirit of collaboration translates into an open culture and a top five position in collaborating with advanced industries. Fundamental knowledge enables us to design solutions for the highly complex problems of today and tomorrow.

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 Biomedical Engineering (BmE) is at the forefront of groundbreaking research in Regenerative Engineering & Materials, Chemical Biology, and Biomedical Imaging & Modelling. Our primary goal is to educate the next generation of biomedical engineers, who are knowledgeable, socially aware, entrepreneurial, and responsible professionals. To do so, we provide a safe and inclusive environment that challenges students and staff to learn, explore, and develop their talents. The close connection between science, engineering, education, students, and staff is a key principle of our department, where new scientific insights and developments are quickly integrated into education, and students learn and are inspired by biomedical challenges. The combination of engineering and life sciences positions us well to make significant contributions to several exciting and promising research areas, including immune-engineering and regenerative medicine, systems and synthetic biology, the application of AI in molecular design, image analysis, and medical decision support. The scientific questions we address are inspired by fundamental challenges in biomedicine and healthcare, and we actively pursue the translation of scientific insights and new therapeutic and diagnostic approaches in partnership with healthcare providers and the medical industry, and by promoting biotech entrepreneurship among our staff.

Cluster Regenerative Engineering & Materials (REM) aims to investigate and deliver cutting-edge engineering solutions for the field of regenerative medicine. This includes basic and applied research as well as methodological innovations in the fields of tissue engineering, organ regeneration, engineered disease modelling, biomaterials & biofabrication, computational modelling, and data sciences. Current research focuses on cardiovascular, orthopaedic, and soft connective tissues, as well as the mechanobiological and immunological aspects of tissue and organ development, adaptation, degeneration, and regeneration. Cluster members are nationally and internationally highly competitive. Research is often performed in close collaboration with clinical partners, patient organizations, or industry. The cluster's educational curriculum includes all relevant basic and applied courses in (computational) tissue engineering, regenerative medicine, biomechanics, and numerical methods at the Bachelor’s and Master’s levels, with a keen eye for frontier engineering approaches. Moreover, the Department runs a joint master track in Regenerative Medicine and Technology with the University Medical Center Utrecht.

Collaborations and opportunities

The Dutch regenerative medicine field is extensive and internationally leading. The REM cluster at TU/e is positioned very well within the Dutch landscape, with excellent visibility and connections to other groups and institutes. Cluster members are involved in the Institute for Complex Molecular Systems, the Materials Technology Institute, and EAISI, TU/e's cross-departmental institute for Artificial Intelligence. REM staff take leading positions in several national and international public-private consortia, a gravitation program, a Summit program, and a National Growth Fund in regenerative medicine. Many BmE staff have obtained prestigious personal grants such as Veni/Vidi/Vici, ERC Starting, Consolidator and Advanced grants.

Regenerative medicine is a topic of common interest across research groups in the Department of Biomedical Engineering, such as Chemical Biology, Biomaterials Science, and Photoacoustics & Ultrasound. Within TU/e, collaborations exist with the Department of Mechanical Engineering, for example, on lab-on-chip developments, and with the Department of Mathematics and Computer Science on methodological advancements of AI.

Information
Do you recognize yourself in this profile and would you like to know more? Please contact Prof.dr. Keita Ito (k.ito@tue.nl) or Dr.ir. Sandra Loerakker (s.loerakker@tue.nl).

Visit our website for more information about the application process or the conditions of employment. You can also contact Marjon Temmink at HRadviceBME@tue.nl.

Curious to hear more about what it's like as a professor at TU/e? Please watch the video.

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

Application
This vacancy is part of the Irène Curie Fellowship and is currently only open to female candidates. Male applicants will not be considered for the position.

We invite you to submit a complete application. 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.
• Description of your scientific interests and plans (1-2 pages).
• Statement of your teaching goals and experience (1-2 pages).

Ensure that you submit all the requested application documents. Please note that incomplete applications may not be considered and could be rejected.

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 Organic Iontronic Neuromorphic Devices and Circuits

Neuromorphic hardware promises efficient learning and control, yet nearly all existing platforms rely on rigid, silicon-based electronics and electron-only information carriers. In contrast, biological systems compute and control with hydrated ions, in soft and dynamic environments. Organic mixed ionic–electronic conductors (OMIECs) and iontronic circuits now offer an opportunity to move beyond electronics that imitate the brain towards soft, ion-based devices and circuit architectures that can be physically co-located with sensors, actuators and even biological tissues.

We will develop a fundamentally new class of organic iontronic neuromorphic devices and circuits such as memory elements and spiking neurons, and explore how they can implement learning control at the interface between the human body and intelligent robotic systems. The project builds on our previous work on organic electrochemical synapses, biohybrid synapses modulated by neurotransmitters, neuromorphic biosensors with on-chip learning and progressive hardware backpropagation in ECRAM arrays developed in our group (see: van de Burgt group which is part of the Microsystems Section). These achievements provide a unique platform to now ask deeper questions about control and computation with ions at the physical interface to the body.

The overall goal of this PhD project is:
To develop organic iontronic neuromorphic devices and circuits for smart adaptive biosensors and control

Embedding
The PhD student will be directly supervised by prof. Yoeri van de Burgt, Professor in Neuromorphic Engineering, within the Microsystems section, headed by prof. Jaap den Toonder. Microsystems is part of the Institute for Complex Molecular Systems (ICMS). The Microsystems section manages the Microfab lab, a state-of-the-art micro fabrication facility that houses a range of micro-manufacturing technologies.

Assistant-Associate Professor in Biomechanics of Regenerative Implants

As an assistant/associate professor, you will establish a new research direction in the field of Regenerative Engineering & Materials (REM), with a strong emphasis on biomechanics of regenerative implants. Preference will be given to those focusing on hard tissues. Your research profile complements the existing areas of research within the REM cluster and the Department of Biomedical Engineering. This should include expertise in computational biomechanics and preferably experience/expertise in data-driven and hybrid modeling approaches. In addition to your own research, there are ample opportunities to collaborate on multidisciplinary research projects. You will take the lead in attracting funding for your research and will build connections and collaborations with researchers and research programs within the cluster, the department, TU/e, and internationally. You will develop, teach, and continuously improve courses for the BSc, MSc, and PhD educational programs in the Biomedical Engineering department, particularly in the area of biomechanics. You will supervise and mentor BSc, MSc, EngD, and PhD students, empowering the next generation of engineers, and you will conduct your research in our shared laboratories and computational facilities, where we collectively support one another in accessing advanced infrastructure.

PhD on Multi-Faceted Visual Process Analytics

Introduction
Are you eager to research and develop Visual Analytics techniques for Event Sequence exploration and analysis? Are you curious how to combine and explore the synergy between Visualization and Process Mining? In this project we aim to transform the way we analyze and visualize complex processes.

Job Description
The field of process mining, a branch of business process management, revolves around discovering, analyzing, and optimizing business processes. It does so by extracting insights from event logs, structured records that capture sequences of activities, such as steps in a loan approval workflow, product purchases by customers, or patient journeys across hospitals. However, traditional process mining techniques focus primarily on control-flow, which describes the chain of activities. This singular focus often neglects other dimensions of processes, such as the time between activities and the time required for specific steps, the spatial distribution of tasks across locations, or the intricate relationships between resources and attributes involved in the processes. For example, in a supply chain scenario, understanding delays, warehouse locations, and inventory attributes is crucial, but often omitted in basic control-flow analysis. Process mining, as it stands today, is primarily based on computational techniques and algorithms to analyze and optimize processes. Methods such as process discovery, conformance checking, and performance analysis rely on algorithmic approaches to extract patterns, detect deviations, and identify inefficiencies from event logs. Although these techniques have proven effective in providing data-driven insights, they often fail to use visualization as a powerful means of interpretation and communication. Most process mining tools provide static and linear representations, such as process models (DFGs, BPMN) or Gantt charts, which are primarily suited for experts familiar with these abstractions. This limited use of visualization overlooks the potential for dynamic, interactive visual tools that can make complex process data accessible to a broader audience, enabling intuitive exploration and deeper understanding of multi-faceted process attributes, such as time, resources, and contextual dependencies and correlations.

In contrast, the field of visual analytics focuses on developing tools and techniques to support the interpretation of complex, multi-dimensional data. It provides concepts and techniques to explore and analyze event sequences, allowing patterns and anomalies to emerge intuitively. For example, visualizations such as timelines, Sankey diagrams, or network diagrams make it possible to uncover dependencies and bottlenecks in event sequences. Despite their shared goal of deriving actionable insights from event sequence data, process mining and visual analytics have largely operated in parallel, leaving significant opportunities for synergy unexplored.

By integrating the two domains, process mining can benefit from visual analytics’ expertise in handling multi-faceted data. Visualizations that incorporate temporal, spatial, and relational aspects can unlock deeper insights into processes. Conversely, visual analytics can leverage process mining techniques to enhance guidance and evaluation during data exploration. For instance, capturing event logs while users interact with visualization tools can provide valuable feedback to refine analytical techniques.

The challenge lies in merging these disciplines effectively, combining their strengths to fully realize the potential of multi-faceted data for visual process analytics. This project tackles this open problem, aiming to create a unified framework that harmonizes these complementary fields, transforming the way we analyze and visualize complex processes.

In this project, the focus is on developing Visual Analytics techniques for event sequence exploration and analysis to enable Multi-Faceted Visual Process Analytics. The project is performed within the Visualization cluster under the supervision of dr.ir. Stef van den Elzen and dr. Fernando Paulovich.

The visualization cluster (https://research.tue.nl/en/organisations/visualization-3) at TU/e has a strong track record in visualization and visual analytics for high-dimensional data. It has generated several award-winning contributions at major visualization conferences (IEEE VIS, IEEE InfoVis, IEEE VAST, EuroVis); several successful start-up companies (MagnaView – now UiPath and SynerScope); and a number of techniques that are used on a large scale worldwide.

Job Requirements
We are looking for a candidate who meets the following requirements:

• You are enthusiastic about research in Visual Analytics, Event Sequence Visualization, and Process Mining.
• You have experience with or a strong background in Visualization or Visual Analytics. Preferably you finished a master’s in Computer Science, (Applied) Mathematics, or Electrical Engineering.
• Expertise in the field of Process Mining/Event Visualization is a plus but not mandatory.
• You have strong programming skills in object-oriented GUI languages (Qt/C++, Java, Python,...)
• You have good communication skills and are able to work in a multidisciplinary team.
• You are creative, critical, analytical, hardworking, and persistent.
• You have a good command of the English language (knowledge of Dutch is not required).

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.
• 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.

Information
Do you recognize yourself in this profile and would you like to know more?
Please contact the hiring manager Stef van den Elzen, Assistant Professor, s.j.v.d.elzen@tue.nl.

Visit our website for more information about the application process or the conditions of employment. You can also contact HRServices.MCS@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.

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 Chapter 8 of the National Knowledge Security Guidelines.
• Please do not contact us for unsolicited services.