PhD in Safe AI-based Control

Introduction
Are you fascinated by how machine learning can enhance control without compromising safety or stability? As a PhD candidate, you will develop scalable methods for expressive and flexible neural controllers for complex systems that are safe and verifiable by design.

Job Description
Neural networks can provide the flexibility needed to control increasingly complex dynamical systems, but their opaque and nonlinear behavior makes it difficult to guarantee safety and stability. How can we exploit the expressive power of machine learning without compromising the rigorous guarantees required in safety-critical control applications?

In this PhD project, you will develop methods for the analysis, verification, and design of neural-network-based controllers. Rather than treating safety and stability as properties to be assessed only after training, you will investigate safety- and verification-by-design approaches that incorporate certifiable properties directly into the controller architecture and learning process.

This project offers a unique opportunity to work at the intersection of machine learning and control theory. You will develop rigorous theory and scalable computational methods for certifying closed-loop safety and stability, with potential directions including control barrier and Lyapunov functions, quadratic constraints, semidefinite programming, and neural-network architectures with intrinsic stability or robustness properties. You will also investigate how physical insight, prior system knowledge, and stabilizing baseline controllers can be combined with learning to improve performance while retaining rigorous guarantees. The developed methods will be evaluated on benchmark problems and more realistic scenarios involving complex dynamical systems.

You will join the Control Systems Technology group in the Department of Mechanical Engineering. The group offers an open and collaborative environment that combines fundamental and applied research. Its expertise spans data-driven modelling of dynamical systems, control of complex and uncertain systems, motion control for high-tech systems, model predictive, networked, supervisory, neuromorphic, and learning-based control, cyber-physical systems, and optimization. This research is reinforced by close collaborations with industry. You will receive close scientific supervision while having the freedom to shape your research direction, present your work at international conferences, and develop as an independent researcher. Your work will contribute to the foundations of trustworthy artificial intelligence for control and support the reliable use of learning-based controllers in areas such as robotics, motion control, and energy systems.

Job Requirements

• A master’s degree (or an equivalent university degree) in Systems and Control, Control Engineering, Engineering Cybernetics, Mechanical Engineering, Electrical Engineering, Computer Science, Mechatronics, Artificial Intelligence, or a closely related field.
• A strong interest in control theory, machine learning, and safety-critical systems.
• A research-oriented and mathematically rigorous mindset.
• Ability to work independently and in interdisciplinary collaborations.
• 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. € 3,204 - max. € 4,051 gross base salary per month (full-time)).
• In addition to your base salary, you will receive an 8% holiday allowance and an 8.3% year-end bonus, both calculated based on your annual gross base salary.
• As a TU/e employee, you participate in the ABP pension scheme, providing retirement pension and pension benefits for surviving dependents and occupational disability. TU/e pays 70% of the pension premium, while employees contribute the remaining 30%.
• 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, and on-campus children's day care.
• Unlimited access to the modern on‑campus TU/e Student Sports Center at an exceptionally affordable rate.
• We support your wellbeing with free 24/7 access to OpenUp, providing you and your family with mental health support, expert guidance, and online training.
• An allowance for commuting, working from home and internet costs.
• A Staff Immigration Team and a tax compensation scheme (the Expat Scheme) 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.

Information
Do you recognize yourself in this profile and would you like to know more? Please contact the hiring manager Dr. Patricia Pauli, Assistant Professor, p.d.pauli@tue.nl.

Visit our website for more information about the application process. You can also contact HR Services, 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.

PhD in Safe AI-based Control

Neural networks can provide the flexibility needed to control increasingly complex dynamical systems, but their opaque and nonlinear behavior makes it difficult to guarantee safety and stability. How can we exploit the expressive power of machine learning without compromising the rigorous guarantees required in safety-critical control applications?

In this PhD project, you will develop methods for the analysis, verification, and design of neural-network-based controllers. Rather than treating safety and stability as properties to be assessed only after training, you will investigate safety- and verification-by-design approaches that incorporate certifiable properties directly into the controller architecture and learning process.

This project offers a unique opportunity to work at the intersection of machine learning and control theory. You will develop rigorous theory and scalable computational methods for certifying closed-loop safety and stability, with potential directions including control barrier and Lyapunov functions, quadratic constraints, semidefinite programming, and neural-network architectures with intrinsic stability or robustness properties. You will also investigate how physical insight, prior system knowledge, and stabilizing baseline controllers can be combined with learning to improve performance while retaining rigorous guarantees. The developed methods will be evaluated on benchmark problems and more realistic scenarios involving complex dynamical systems.

You will join the Control Systems Technology group in the Department of Mechanical Engineering. The group offers an open and collaborative environment that combines fundamental and applied research. Its expertise spans data-driven modelling of dynamical systems, control of complex and uncertain systems, motion control for high-tech systems, model predictive, networked, supervisory, neuromorphic, and learning-based control, cyber-physical systems, and optimization. This research is reinforced by close collaborations with industry. You will receive close scientific supervision while having the freedom to shape your research direction, present your work at international conferences, and develop as an independent researcher. Your work will contribute to the foundations of trustworthy artificial intelligence for control and support the reliable use of learning-based controllers in areas such as robotics, motion control, and energy systems.

Postdoc in Attacks, Countermeasures & Eavesdropping on Quantum Key Distribution

Introduction
Are you passionate about keeping communications networks secure and trustworthy? Are you eager to explore attacks and countermeasures for QKD systems and to help ensure they can deliver the promised security advantages? Join us to work on QKD for quantum safe communications in future networks.

Job Description
The security of modern communications is threatened by advances in quantum computing which have the potential to break common methods for establishing and distributing cryptographic keys. Unless networks can be upgraded to new, quantum safe methods the trust in communications networks which modern society so heavily relies on for all aspects of life cannot be maintained. Post-quantum cryptography and quantum key distribution have been shown to be viable options to provide key agreement and distribution that is safe against attackers enabled by quantum computers. However, the implementations of QKD may introduce weaknesses not accounted for in security proofs, leaving systems vulnerable to side-channel and other types of attacks.

In this PostDoc position you will explore existing and novel attacks on QKD systems and develop countermeasures and analyze their security implications. You will create a simulation and analysis framework to validate and evaluate existing and novel attacks and countermeasures, and you will work on establishing standardized protocols for QKD security testing as well as attach and countermeasure evaluation. You will further develop hardware attack systems designed to eavesdrop on or otherwise compromise security of existing QKD implementations. In short, this PostDoc focuses on evaluating attacks and countermeasures for QKD systems and developing a hardware attack system to evaluate existing QKD implementations.

In this PostDoc you will become part of the quantum communications team at TU/e and will work very closely with industrial partners. You will be embedded in the Quantum & Terahertz Systems (QTS) team within the Electro-Optical Communications (ECO) group of the Department of Electrical Engineering at TU/e. Within QTS you will work within a dynamic team of approximately thirty researchers and as part of ECO will be part of one of the leading groups on optical communications and networking with more than one hundred researchers. You will have the opportunity to work with and in the extensive laboratory facilities of the ECO group as well as the Quantum Communications Testbed NL (QuCT NL).

Job Requirements

• Motivated researcher, with a PhD in quantum communications, quantum security, or a comparable domain (typically in Electrical Engineering or Computer Science).
• Experience with QKD protocol design and implementation as well as protocol and implementation security analysis.
• Experience with quantum key distribution at both theoretical and experimental level.
• Ability to conduct high quality academic research, reflected in demonstratable outputs.
• A team player who enjoys coaching PhD and Master's students and working in a dynamic, interdisciplinary team.
• A proven ability to manage complex projects to completion on schedule.
• A proven ability to liaise with internal and external project stakeholders and partners to develop common understanding and establish agreed designs.
• Excellent (written and verbal) proficiency in English, good communication and leadership skills.

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 2 years with the possibility of extension.
• Salary in accordance with the Collective Labour Agreement for Dutch Universities, scale 10, ranging from € 4,422 (step 4) to € 5,760 gross base salary per month (full-time).
• In addition to your base salary, you will receive an 8% holiday allowance and an 8.3% year-end bonus, both calculated based on your annual gross base salary.
• As a TU/e employee, you participate in the ABP pension scheme, providing retirement pension and pension benefits for surviving dependents and occupational disability. TU/e pays 70% of the pension premium, while employees contribute the remaining 30%.
• High-quality training programs on general skills, didactics and topics related to research and valorization.
• An excellent technical infrastructure, and on-campus children's day care.
• Unlimited access to the modern on‑campus TU/e Student Sports Center at an exceptionally affordable rate.
• We support your wellbeing with free 24/7 access to OpenUp, providing you and your family with mental health support, expert guidance, and online training.
• Partially paid parental leave and an allowance for commuting, working from home and internet costs.
• A TU/e Postdoc Association that helps you to build a stronger and broader academic and personal network, and offers tailored support, training and workshops.
• A Staff Immigration Team is available for international candidates, as are a tax compensation scheme (the Expat Scheme) and a compensation for moving expenses.

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 Quantum Communications Testbed NL (QuCT NL) is a leading facility and infrastructure for the development and test of quantum safe communications and future quantum networks. This facility is fully operated by TU/e and forms the backbone of both academic research and research and development for and with industrial partners. It consists of a field-deployed network with quantum key distribution and quantum safe communications infrastructure from a multitude of vendors and implementing a variety of security mechanisms and protocols.

Information
Do you recognize yourself in this profile and would you like to know more? Please contact the hiring manager dr. Simon Rommel, Assistant Professor, s.rommel@tue.nl or +31 40 247 5704.

Visit our website for more information about the application process.

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 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.
• List of up to five self-selected ‘best publications’.

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.

Postdoc in Attacks, Countermeasures & Eavesdropping on Quantum Key Distribution

The security of modern communications is threatened by advances in quantum computing which have the potential to break common methods for establishing and distributing cryptographic keys. Unless networks can be upgraded to new, quantum safe methods the trust in communications networks which modern society so heavily relies on for all aspects of life cannot be maintained. Post-quantum cryptography and quantum key distribution have been shown to be viable options to provide key agreement and distribution that is safe against attackers enabled by quantum computers. However, the implementations of QKD may introduce weaknesses not accounted for in security proofs, leaving systems vulnerable to side-channel and other types of attacks.

In this PostDoc position you will explore existing and novel attacks on QKD systems and develop countermeasures and analyze their security implications. You will create a simulation and analysis framework to validate and evaluate existing and novel attacks and countermeasures, and you will work on establishing standardized protocols for QKD security testing as well as attach and countermeasure evaluation. You will further develop hardware attack systems designed to eavesdrop on or otherwise compromise security of existing QKD implementations. In short, this PostDoc focuses on evaluating attacks and countermeasures for QKD systems and developing a hardware attack system to evaluate existing QKD implementations.

In this PostDoc you will become part of the quantum communications team at TU/e and will work very closely with industrial partners. You will be embedded in the Quantum & Terahertz Systems (QTS) team within the Electro-Optical Communications (ECO) group of the Department of Electrical Engineering at TU/e. Within QTS you will work within a dynamic team of approximately thirty researchers and as part of ECO will be part of one of the leading groups on optical communications and networking with more than one hundred researchers. You will have the opportunity to work with and in the extensive laboratory facilities of the ECO group as well as the Quantum Communications Testbed NL (QuCT NL).

PhD in Forward Error Correction for Optical Quantum-Secured Networks

Introduction
Ever wondered what keeps your data flawless, and secret, as it travels through an optical fibre, even against the quantum computers on the horizon?
The answer is error-correcting codes: clever maths that repairs errors invisibly, in real time. As AI pushes data demand ever higher and quantum computers threaten today's encryption, future optical links will need to be faster and more secure than ever, and these codes are central to both.
Wanna help shape this key technology behind reliable and secure optical communications? Come join us as a PhD student, designing the error-correcting codes behind tomorrow's quantum optical networks, within the European QuNEST network.

Job Description
You will analyse and design advanced Forward Error Correction (FEC) codes for high-throughput optical communication systems, whether building on established families such as LDPC, polar, and spatially-coupled codes or inventing entirely new ones. A key application of your work will be information reconciliation for quantum key distribution (QKD), where you will adapt both the codes and their decoders to the specific security and performance requirements of QKD protocols. Beyond QKD, you are encouraged to explore open problems in coding for classical optical channels, such as low-power schemes for data-centre interconnects or code constructions for nonlinear fibre transmission. The role is deliberately broad within the FEC space, leaving room to pursue the directions that best match your interests and strengths.
You will join the Information and Communication Theory Lab (ICT Lab) at TU/e, an international and diverse group focused on information and communication theory and its applications including classical and quantum optical and wireless communication systems.
This PhD sits within "QuNEST – Quantum Enhanced Optical Communication Network Security Doctoral Training," a Horizon Europe Marie Skłodowska-Curie Actions (MSCA) Doctoral Network built on a consortium of six academic and eleven industrial partners across seven European countries. Best of all, you will not do this alone: you will be part of a vibrant, international cohort of 11 doctoral candidates who train, travel, and tackle the challenges of quantum-secure communication together, meeting regularly at joint schools, workshops, and network events across Europe. Alongside this, you will benefit from cross-disciplinary training spanning communications, quantum physics, and photonics, and spend time abroad with host institutions, typically for 2–6 months.
Your work will feed directly into the next generation of secure optical communication infrastructure, an area of rising societal and industrial importance as data networks face growing demands for both capacity and protection.
You will be supervised by Dr Gabriele Liga at TU/e (https://www.tue.nl/en/research/researchers/gabriele-liga), and will carry out secondments at various European institutions, such as the Karlsruhe Institute of Technology (Germany) with Prof. Laurent Schmalen or Nokia Bell Labs (Paris, France) with Dr Amirhossein Ghazisaeidi.

MSCA-DN Eligibility Rules

• The candidate cannot already be in possession of a doctoral degree at the date of recruitment.
• Mobility rule: the candidate must not have resided or carried out their main activity (work, studies, etc.) in the Netherlands for more than 12 months in the 36 months immediately before their recruitment date.

Job Requirements

• A master’s degree (or an equivalent university degree) in Electrical Engineering, Computer Science, Applied Mathematics, or a related field.
• A strong foundation in communication theory and at least minimal exposure to coding theory and/or information theory. Solid knowledge or prior work on error-correcting codes for communication systems is considered a plus.
• A determination to pursue excellence through hard work.
• A clear inclination toward theoretical work and a research-oriented attitude.
• Proficiency in programming languages such as Python, MATLAB, or C/C++.
• Prior exposure to quantum information, quantum optics, or QKD is welcomed but not required — we are equally interested in candidates with a strong classical coding/communication-theory background who are keen to apply their skills to a new domain.
• Ability to work in an interdisciplinary team and an interest in collaborating with industrial partners.
• A willingness to develop your teaching skills and coach students.
• A good command of spoken and written English (B2+ 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. € 3,204 - max. € 4,051 gross base salary per month (full-time)).
• In addition, as this is a Marie Skłodowska-Curie Actions (MSCA) Doctoral Candidate position, your gross salary and benefits (including a family allowance, if eligible) will be set in accordance with MSCA regulations for Doctoral Candidates, on top of the standard TU/e PhD arrangements listed below.
• In addition to your base salary, you will receive an 8% holiday allowance and an 8.3% year-end bonus, both calculated based on your annual gross base salary.
• As a TU/e employee, you participate in the ABP pension scheme, providing retirement pension and pension benefits for surviving dependents and occupational disability. TU/e pays 70% of the pension premium, while employees contribute the remaining 30%.
• 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, and on-campus children's day care.
• Unlimited access to the modern on‑campus TU/e Student Sports Center at an exceptionally affordable rate.
• We support your wellbeing with free 24/7 access to OpenUp, providing you and your family with mental health support, expert guidance, and online training.
• An allowance for commuting, working from home and internet costs.
• A Staff Immigration Team and a tax compensation scheme (the Expat Scheme) 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.

Eindhoven University of Technology (TU/e) is an equal opportunity employer committed to diversity, inclusion, and gender balance. We evaluate all applicants on merit, regardless of gender, ethnic origin, religion, age, sexual orientation, or disability. We welcome applications from candidates of all backgrounds and underrepresented groups.

Information
Do you recognize yourself in this profile and would you like to know more? Please contact Dr. Gabriele Liga, g.liga@tue.nl.

Visit our website for more information about the application process.

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.

"#EUfunded This is an EU funded project, named QuNEST – Quantum Enhanced optical communication, with project number 101120422, within program HE / MSCA*."

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

• 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 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.
• Full academic transcripts for your Master’s and Bachelor’s programmes.
• As this position is funded under the QuNEST Marie Skłodowska-Curie Actions (MSCA) Doctoral Network, please also include a brief eligibility statement indicating your country/countries of main activity (work, studies, etc.) and residence over the last 3 years, with exact dates, to verify MSCA mobility eligibility.

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.