PhD in AI-driven Fair Energy Curtailment Policies

Introduction
Are you interested in tackling one of the most urgent challenges of the energy transition and pushing the boundaries of AI integrated distributed optimization for large‑scale energy networks? As a PhD candidate, you will help design AI‑driven control algorithms that allow thousands of distributed energy resources to coordinate locally while ensuring the grid remains stable, efficient, and fair. You will explore probabilistic curtailment policies, develop scalable multi‑agent decision‑making methods, and work with real‑world data to create solutions that can be deployed in tomorrow’s electricity systems. This position offers a unique opportunity to shape both cutting‑edge theory and real societal impact.

Job Description
The rapid growth of Distributed Energy Resources (DERs), such as rooftop photovoltaics (PV) is transforming electricity distribution networks. While essential for decarbonization, this transition creates new operational challenges. Local electricity networks can become congested when many producers inject power simultaneously or due to electrification of consumption, such as heat pumps (HPs) and electric vehicles (EVs). This project aims to develop fair and reliable AI-based control methods for managing congestion in electricity distribution networks. The core idea is to embed clear and interpretable notions of fairness directly into the algorithms that determine how much energy different prosumers may inject during congestion.

The proposed project aims to advance fundamental science at the intersection of electrical power engineering, control, machine learning, and sociotechnical design. It seeks to redefine how societal and economic objectives are formalized and enforced in intelligent control systems. Achieving this requires close interdisciplinary collaboration.

You will be embedded in the Control Systems group at TU/e, contributing to its research program on intelligent and responsible control of networked systems.

You will collaborate closely with experts in responsible AI, energy systems, and distributed control, working across departments in an interdisciplinary team.

Your work will directly contribute to a fairer, more resilient, and more sustainable energy system. By developing algorithms that help DSOs manage congestion transparently and equitably, you support the acceleration of renewable energy integration and strengthen public trust in the energy transition.

• Review literature on congestion management: Study state‑of‑the‑art methods for mitigating grid congestion, with a focus on proactive and distributed control strategies in modern distribution networks.
• Analyze distributed optimization methods: Investigate existing distributed and decentralized optimization algorithms (e.g., consensus‑based, ADMM‑type, multi‑agent MPC) and assess their suitability for large‑scale distributed energy resources coordination.
• Develop probabilistic curtailment policies: Explore raffle‑based and weighted probabilistic allocation schemes grounded in fairness theory, and translate them into implementable control rules.
• Design fairness‑aware distributed controllers: Formulate distributed control algorithms that integrate fairness constraints while ensuring scalability, stability, and robustness.
• Model uncertainty in renewable generation: Incorporate stochastic models of PV output, demand fluctuations, and network variability into the control framework.
• Evaluate robustness of control policies: Assess how the proposed algorithms perform under forecasting errors, model mismatches, and communication delays.
• Implement multi‑agent coordination mechanisms: Develop local decision‑making rules that allow DERs to coordinate with minimal communication while achieving global fairness and efficiency.
• Simulate large‑scale distribution networks: Use realistic feeder models and open datasets to test algorithmic performance under diverse operating conditions.
• Collaborate with energy system experts: Work closely with colleagues in control, AI, and electrical engineering to align algorithmic design with real‑world grid constraints.
• Validate methods on real‑world data: Apply the developed algorithms to datasets from Dutch DSOs to ensure practical relevance and societal impact.

This PhD position is part of the project "Responsible AI for Fair and Efficient Control of Energy Systems (RAICES)“ (https://www.tue.nl/en/research/institutes/eindhoven-artificial-intelligence-systems-institute/ai-research/eaisi-emdair-program)

Job Requirements

• A master’s degree (or an equivalent university degree) in Electrical Engineering, Mechanical Engineering, Mathematics, Physics.
  
  • In case you are still doing your MSc in the field listed above, please indicate your expected graduation date in the cover letter.
• A research-oriented attitude with curiosity.
• Ability 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? Visit our website for more information about the application process. You can also contact Dr. Giulia De Pasquale (g.de.pasquale@tue.nl) or Dr. Nikolaos Paterakis (n.paterakis@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.
• A copy of the MSc thesis, if written in English, or a 2-pages summary otherwise.

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 in AI-driven Fair Energy Curtailment Policies

The rapid growth of Distributed Energy Resources (DERs), such as rooftop photovoltaics (PV) is transforming electricity distribution networks. While essential for decarbonization, this transition creates new operational challenges. Local electricity networks can become congested when many producers inject power simultaneously or due to electrification of consumption, such as heat pumps (HPs) and electric vehicles (EVs). This project aims to develop fair and reliable AI-based control methods for managing congestion in electricity distribution networks. The core idea is to embed clear and interpretable notions of fairness directly into the algorithms that determine how much energy different prosumers may inject during congestion.

The proposed project aims to advance fundamental science at the intersection of electrical power engineering, control, machine learning, and sociotechnical design. It seeks to redefine how societal and economic objectives are formalized and enforced in intelligent control systems. Achieving this requires close interdisciplinary collaboration.

You will be embedded in the Control Systems group at TU/e, contributing to its research program on intelligent and responsible control of networked systems.

You will collaborate closely with experts in responsible AI, energy systems, and distributed control, working across departments in an interdisciplinary team.

Your work will directly contribute to a fairer, more resilient, and more sustainable energy system. By developing algorithms that help DSOs manage congestion transparently and equitably, you support the acceleration of renewable energy integration and strengthen public trust in the energy transition.

• Review literature on congestion management: Study state‑of‑the‑art methods for mitigating grid congestion, with a focus on proactive and distributed control strategies in modern distribution networks.
• Analyze distributed optimization methods: Investigate existing distributed and decentralized optimization algorithms (e.g., consensus‑based, ADMM‑type, multi‑agent MPC) and assess their suitability for large‑scale distributed energy resources coordination.
• Develop probabilistic curtailment policies: Explore raffle‑based and weighted probabilistic allocation schemes grounded in fairness theory, and translate them into implementable control rules.
• Design fairness‑aware distributed controllers: Formulate distributed control algorithms that integrate fairness constraints while ensuring scalability, stability, and robustness.
• Model uncertainty in renewable generation: Incorporate stochastic models of PV output, demand fluctuations, and network variability into the control framework.
• Evaluate robustness of control policies: Assess how the proposed algorithms perform under forecasting errors, model mismatches, and communication delays.
• Implement multi‑agent coordination mechanisms: Develop local decision‑making rules that allow DERs to coordinate with minimal communication while achieving global fairness and efficiency.
• Simulate large‑scale distribution networks: Use realistic feeder models and open datasets to test algorithmic performance under diverse operating conditions.
• Collaborate with energy system experts: Work closely with colleagues in control, AI, and electrical engineering to align algorithmic design with real‑world grid constraints.
• Validate methods on real‑world data: Apply the developed algorithms to datasets from Dutch DSOs to ensure practical relevance and societal impact.

This PhD position is part of the project "Responsible AI for Fair and Efficient Control of Energy Systems (RAICES)“ (https://www.tue.nl/en/research/institutes/eindhoven-artificial-intelligence-systems-institute/ai-research/eaisi-emdair-program)

PhD in Flexibility Services from Electrified Process Industry: A Focus on Steam-Heated Processes

Introduction
Do you want to be part of an industry-oriented project and work on flexibility estimation from industrial sites?
The envisioned research is part of the research program Intelligent Energy Systems (IES) performed within the Electrical Energy Systems (EES) group of TU/e. Within the IES program, research is conducted into operation and planning of future sustainable energy systems, with an emphasis on electricity systems, markets and systems integration. This research is performed in two research labs: the Digital power and energy systems lab (EES DigiPES lab) and the Electricity markets and power system optimization lab (EES EMPDO lab). The former focuses on intelligent energy network research, including: demand management and flexibility, digital twinning, data analytics, smart grid ICT architectures and systems integration in multi energy systems. The latter specializes in electricity market design (centralized & decentralized), market products & system services to integrate new technologies, forecasting, market participation strategies and risk management, large-scale, distributed, multi-objective optimization techniques applied to energy markets and power systems and AI for optimization and control in power and energy systems. The EES group has strong ties with industry both nationally and internationally, with several part-time industry researchers working in the group and a large group of strategic collaboration partners.

Recently, the Electrical Energy Systems group received grants for nationally-funded projects in Intelligent Electricity Systems. Therefore, this group currently has multiple vacancies in this field. We are currently looking for researchers with strong energy systems knowledge, electricity, heat, and gas system components and flexibility modelling & simulation, and research software development skills that want to develop cutting-edge knowledge and software for the energy transition.. The focus of the work will be on the application of intelligent software approaches (distributed control systems, distributed optimization, market mechanisms, multi-scale modelling, etc.), in electrical power systems (energy system flexibility coordination, local energy markets, capacity & congestion management, etc.).

Job Description
The decarbonization of the industrial sector is critical to achieving climate neutrality. Steam-based industries, such as chemical manufacturing, food processing, and paper production, are among the most energy-intensive and carbon-emitting sectors. Electrification of thermal processes, particularly through the integration of industrial heat pumps, presents a promising pathway to reduce emissions while offering flexibility services to the energy system.

At the same time, the increasing penetration of variable renewable energy such as wind and solar creates a pressing need for flexibility services to balance supply and demand. Industrial processes, with their significant thermal inertia and storage potential, can provide valuable flexibility to the power grid. However, the integration of such services into steam-heated industrial processes remains a challenge, especially when considering the role of large-scale heat pumps, industrial heat storage, and heat recovery technologies as both decarbonization and flexibility enablers. The challenge rises from several factors affecting the daily operation of the factories as well as the investment requirements that might not be compensated accordingly when the derived flexibility is offered to the grid/market. In this regard, this PhD focuses on optimizing the use of flexibility in electrified process plants by leveraging dynamic behaviors and market participation.

With the above premises, the main objectives of this study are

1. Characterize the thermal demand profiles of steam-based industrial processes and identify opportunities for electrification. => Baseline optimisation
2. Assess the technical feasibility and performance of industrial heat pumps in steam generation and recovery. => Design options and technology inclusions
3. Develop models to quantify the flexibility potential of electrified steam systems, including load shifting, demand response, and ancillary services. => Energy use optimisation
4. Assess the techno-economic feasibility of providing flexibility services from electrified steam processes. => Business assessment
5. Grid impact assessment and capacity management approaches in an industry-infused network with integrated industrial flexibility services. => Grid impact assessment

In order to achieve these goals the following tasks would shape the work plan of the PhD:

Energy Portfolio Creation: A comprehensive estimation of the available flexibility within electrified process plants should be undertaken. This task involves a detailed assessment of the various processes and identifying potential extractable flexibility from electrified thermal systems. The goal is to quantify the extent to which these processes can be adjusted or modulated, taking into account the operational constraints and requirements. This estimation will include analyzing the energy consumption patterns, identifying peak and off-peak periods, and understanding the critical operational parameters that must remain stable. The maximum achievable flexibility that can be harnessed without compromising the efficiency, productivity, and overall operational stability of the process plants can be determined. This rigorous analysis will provide a clear picture of the flexibility potential and set the stage for implementing effective flexibility services tailored to the dynamic behavior of the process industry.

Flexibility service definition and potential calculations: The next task would be to identify and define flexibility services that are specifically tailored to the dynamic nature of process industries. This involves a thorough examination of the various industrial processes to determine how they can be adapted or modulated to provide flexibility services. The approach includes a detailed analysis of the operational characteristics and requirements of each process, aiming to understand the inherent dynamic behaviors and how they can be leveraged to create flexibility.

Through exploring different strategies for modulating processes, such as adjusting production schedules, varying energy consumption rates, and implementing advanced control systems, new definitions for flexibility services from industry will be provided. This definition would consider the type, feature, and characteristics of the service from both industry side and market side, meaning the conditions that the plant needs to follow to provide such services as well as the market conditions to which the service is offered.

Evaluating implementation potential: In this task, the energy market status for the process industry will be analysed to determine the viability of electrified processes considering the increased required electric demand and the new possibilities of saving energy costs using the flexibility of electrified thermal systems. To achieve this, the current status of the markets will be analysed to assess the possibility of incorporating industrial flexibility. Different revenue schemes will be considered to deploy industrial flexibility as a product in the market. The flexibility trade with the characteristics of flexibility from industrial processes will be analysed. The energy market status for both electricity and gas markets will be studied to evaluate the viability of electrification for specific cases and in regard to price growth of electricity and gas. The trade portfolio of an electrified industrial site will be provided with possibilities of energy market participation, flexibility services remuneration, and CO2 to capture revenues.

This PhD is part of an NWO project called “Flexibility in Electric Power from Steam-heated Industrial Processes” (FLEXPower). There are several partners involved in this project including a large distribution system operator, industrial partners, industrial flexibility technology providers, and an applied research institute. The PhD student will be involved in this project, will have the chance to participate in meetings, and have a close collaboration with industry. The study could also benefit from using real data from the industrial partners involved in the project.

Job Requirements
We are looking for a highly motivated and pro-active candidate with good communicative skills and English language proficiency. As a PhD candidate you should have the following qualifications

• A MSc degree related to modelling and analysis of flexibility, energy (electricity, gas, heat) consumption such as electrical or mechanical engineering
• Having a good understanding of energy markets, market products and services.
• Experience in optimization problems, dynamic behavior modelling, and component simulation.
• Excellent modelling skills and skills in scientific programming and/or numerical computing in languages like Python or MATLAB.
• Experience in data-driven modelling, probabilities, and stochastic optimization solutions is an advantage.
• Enthusiasm for open-source software development and motivated to learn basic skills of scientific software engineering.
• Ability to work in an interdisciplinary team and interested in expanding the research to real-world applications through participating in projects.
• Motivated to develop your teaching skills and coach MSc and BSc students.
• Fluent in spoken and written English (C1 level).
• Dutch language skill is an advantage.

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 Nilufar Neyestani, n.neyestani@tue.nl.

Visit our website for more information about the application process. You can also contact HR services, hrservices.ee@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. 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 in Flexibility Services from Electrified Process Industry: A Focus on Steam-Heated Processes

The decarbonization of the industrial sector is critical to achieving climate neutrality. Steam-based industries, such as chemical manufacturing, food processing, and paper production, are among the most energy-intensive and carbon-emitting sectors. Electrification of thermal processes, particularly through the integration of industrial heat pumps, presents a promising pathway to reduce emissions while offering flexibility services to the energy system.

At the same time, the increasing penetration of variable renewable energy such as wind and solar creates a pressing need for flexibility services to balance supply and demand. Industrial processes, with their significant thermal inertia and storage potential, can provide valuable flexibility to the power grid. However, the integration of such services into steam-heated industrial processes remains a challenge, especially when considering the role of large-scale heat pumps, industrial heat storage, and heat recovery technologies as both decarbonization and flexibility enablers. The challenge rises from several factors affecting the daily operation of the factories as well as the investment requirements that might not be compensated accordingly when the derived flexibility is offered to the grid/market. In this regard, this PhD focuses on optimizing the use of flexibility in electrified process plants by leveraging dynamic behaviors and market participation.

With the above premises, the main objectives of this study are

1. Characterize the thermal demand profiles of steam-based industrial processes and identify opportunities for electrification. => Baseline optimisation
2. Assess the technical feasibility and performance of industrial heat pumps in steam generation and recovery. => Design options and technology inclusions
3. Develop models to quantify the flexibility potential of electrified steam systems, including load shifting, demand response, and ancillary services. => Energy use optimisation
4. Assess the techno-economic feasibility of providing flexibility services from electrified steam processes. => Business assessment
5. Grid impact assessment and capacity management approaches in an industry-infused network with integrated industrial flexibility services. => Grid impact assessment

In order to achieve these goals the following tasks would shape the work plan of the PhD:

Energy Portfolio Creation: A comprehensive estimation of the available flexibility within electrified process plants should be undertaken. This task involves a detailed assessment of the various processes and identifying potential extractable flexibility from electrified thermal systems. The goal is to quantify the extent to which these processes can be adjusted or modulated, taking into account the operational constraints and requirements. This estimation will include analyzing the energy consumption patterns, identifying peak and off-peak periods, and understanding the critical operational parameters that must remain stable. The maximum achievable flexibility that can be harnessed without compromising the efficiency, productivity, and overall operational stability of the process plants can be determined. This rigorous analysis will provide a clear picture of the flexibility potential and set the stage for implementing effective flexibility services tailored to the dynamic behavior of the process industry.

Flexibility service definition and potential calculations: The next task would be to identify and define flexibility services that are specifically tailored to the dynamic nature of process industries. This involves a thorough examination of the various industrial processes to determine how they can be adapted or modulated to provide flexibility services. The approach includes a detailed analysis of the operational characteristics and requirements of each process, aiming to understand the inherent dynamic behaviors and how they can be leveraged to create flexibility.

Through exploring different strategies for modulating processes, such as adjusting production schedules, varying energy consumption rates, and implementing advanced control systems, new definitions for flexibility services from industry will be provided. This definition would consider the type, feature, and characteristics of the service from both industry side and market side, meaning the conditions that the plant needs to follow to provide such services as well as the market conditions to which the service is offered.

Evaluating implementation potential: In this task, the energy market status for the process industry will be analysed to determine the viability of electrified processes considering the increased required electric demand and the new possibilities of saving energy costs using the flexibility of electrified thermal systems. To achieve this, the current status of the markets will be analysed to assess the possibility of incorporating industrial flexibility. Different revenue schemes will be considered to deploy industrial flexibility as a product in the market. The flexibility trade with the characteristics of flexibility from industrial processes will be analysed. The energy market status for both electricity and gas markets will be studied to evaluate the viability of electrification for specific cases and in regard to price growth of electricity and gas. The trade portfolio of an electrified industrial site will be provided with possibilities of energy market participation, flexibility services remuneration, and CO2 to capture revenues.

This PhD is part of an NWO project called “Flexibility in Electric Power from Steam-heated Industrial Processes” (FLEXPower). There are several partners involved in this project including a large distribution system operator, industrial partners, industrial flexibility technology providers, and an applied research institute. The PhD student will be involved in this project, will have the chance to participate in meetings, and have a close collaboration with industry. The study could also benefit from using real data from the industrial partners involved in the project.

Postdoc Tx/Rx Isolation Measurements of FMCW radar using a reverberation chamber (TRIM)

Introduction
FMCW radar is key in automotive safety and increasingly important for security applications. For reliable performance it requires sufficient TX‑RX isolation. This project develops techniques for accurately measuring such isolation using a reverberation chamber, leveraging on the expertise on this area available at Antennex, a Dutch SME, and at TU/e.

Job Description
Continuous wave radar with frequency modulation (FMCW radar) has gained traction in automotive safety systems, such as adaptive cruise control and collision avoidance, and it is now a core sensor in self-driving cars. One of the key conditions for the proper functioning of an FMCW radar is guaranteeing sufficient isolation between the transmitting and receiving antenna. An accurate assessment of such isolation is thus of paramount importance in the radar design.

Reverberation chambers are a well-established testing approach both in the field of electromagnetic compatibility as well as for measuring integral radiation quantities of stand-alone antennas (antenna efficiency) and wireless devices (Total Radiated Power, Total Isotropic Sensitivity).

In addition to that, research on antenna radiation pattern measurements in reverberation chambers has started to draw attention. Most methods are based on the property that the line-of-sight component is constantly present in each of the measurements performed on the AUT, and that unwanted scattered components can be averaged out by randomizing the electromagnetic environment in a controllable manner.

Instead, measuring isolation between two arrays, or coupling between measurements inside an array is a completely unexplored area, which will require additional fundamental research.

Your objective in this research project is thus to develop a methodology for accurate and reliable measurement of coupling between antennas in reverberation chambers.

In this project you will cooperate with Robin Radar, a manufacturer of FMCW radar and potential end-user of the results, and with Antennex, a Dutch SME that develops reverberation chambers. Antennex has made fundamental extensions to measurement capabilities in reverberation chambers, for instance, noise figure, FMCW chirp quality and radiation pattern measurements. Enabling isolation measurements would offer a new use case for reverberation chambers, which might be more cost effective compared to the existing anechoic chamber approach.

Job Requirements

• Motivated researcher, with a PhD in Electrical Engineering research, or a comparable domain.
• Experience in the area of radio propagation and antennas, and specifically in antenna measurement techniques is an asset.
• 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.
• 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.
• Salary in accordance with the Collective Labour Agreement for Dutch Universities, scale 10 (min. € 4,241 max. € 5,538).
• A year-end bonus of 8.3% and annual vacation pay of 8%.
• High-quality training programs on general skills, didactics and topics related to research and valorization.
• 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 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 30% facility) 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 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: Stefania Monni, Professor of Array Antenna Technologies for future radar systems, s.monni@tue.nl.

Visit our website for more information about the application process. You can also contact: Kevin Caris, HR-Advisor, Human Resources, k.t.caris@tue.nl.

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.