PhD on Clinical- and Analytical Chemistry

Protein tumor markers (TMs) in blood offer a promising, minimally invasive approach to support clinical decision-making in lung cancer. However, their broad clinical application is currently limited due to the lack of standardized immunoassays, which leads to inconsistent results across analytical platforms and a risk of misclassification when using fixed cut-off levels. Reference measurement procedures (RMPs) provide a solution to this challenge: they are highly accurate, well-characterized methods that serve as traceable standards for biomarker quantification, enabling reliable and reproducible measurements across different assays.

In this PhD project, you will develop RMPs and reference materials (RMs) for several protein TMs to enable harmonized and reproducible measurements across clinical platforms. You will explore advanced analytical approaches, including immunoextraction of full proteins and SISCAPA-based peptide extraction, and develop targeted bottom-up proteomics methods using mass spectrometry. Additionally, you will engineer full proteins and signature peptides for method development, calibration, and quality control. This work will provide the foundation for broader clinical implementation of tumor marker assays and more reliable, minimally invasive diagnostics.

You will work in an interdisciplinary environment at the TU/e Laboratory of Chemical Biology and the Expertise Center Clinical Chemistry Eindhoven (ECCCE), a collaboration between TU/e, Catharina Hospital, and Máxima Medisch Centrum focused on the development and implementation of analytical assays and decision support algorithms in clinical practice. Additionally, the project involves collaborations with large industrial partners such as Roche Diagnostics and SISCAPA. Through this collaboration, you will have access to state-of-the-art analytical facilities and benefit from a strong translational research network connecting fundamental chemical biology, clinical diagnostics, and industrial partners.

You will be working under the supervision of Luc Brunsveld, Volkher Scharnhorst, and a multidisciplinary team with expertise in proteomics, assay development, and clinical translation. You will have access to state-of-the-art facilities and collaborate closely with clinical and industrial partners.

Your research will not only advance the standardization of lung cancer biomarker assays but also contribute to more reliable, minimally invasive diagnostics and improved patient care worldwide.

PhD on Clinical- and Analytical Chemistry

Introduction
Are you eager to advance lung cancer diagnostics by developing standardized biomarker assays using state-of-the-art mass spectrometry? Join us as a PhD candidate and contribute to clinically relevant innovation.

Job Description
Protein tumor markers (TMs) in blood offer a promising, minimally invasive approach to support clinical decision-making in lung cancer. However, their broad clinical application is currently limited due to the lack of standardized immunoassays, which leads to inconsistent results across analytical platforms and a risk of misclassification when using fixed cut-off levels. Reference measurement procedures (RMPs) provide a solution to this challenge: they are highly accurate, well-characterized methods that serve as traceable standards for biomarker quantification, enabling reliable and reproducible measurements across different assays.

In this PhD project, you will develop RMPs and reference materials (RMs) for several protein TMs to enable harmonized and reproducible measurements across clinical platforms. You will explore advanced analytical approaches, including immunoextraction of full proteins and SISCAPA-based peptide extraction, and develop targeted bottom-up proteomics methods using mass spectrometry. Additionally, you will engineer full proteins and signature peptides for method development, calibration, and quality control. This work will provide the foundation for broader clinical implementation of tumor marker assays and more reliable, minimally invasive diagnostics.

You will work in an interdisciplinary environment at the TU/e Laboratory of Chemical Biology and the Expertise Center Clinical Chemistry Eindhoven (ECCCE), a collaboration between TU/e, Catharina Hospital, and Máxima Medisch Centrum focused on the development and implementation of analytical assays and decision support algorithms in clinical practice. Additionally, the project involves collaborations with large industrial partners such as Roche Diagnostics and SISCAPA. Through this collaboration, you will have access to state-of-the-art analytical facilities and benefit from a strong translational research network connecting fundamental chemical biology, clinical diagnostics, and industrial partners.

You will be working under the supervision of Luc Brunsveld, Volkher Scharnhorst, and a multidisciplinary team with expertise in proteomics, assay development, and clinical translation. You will have access to state-of-the-art facilities and collaborate closely with clinical and industrial partners.

Your research will not only advance the standardization of lung cancer biomarker assays but also contribute to more reliable, minimally invasive diagnostics and improved patient care worldwide.

Job Requirements

• A master’s degree in (bio)analytical chemistry, clinical chemistry, biomedical sciences, or related fields.
• Strong interest in biomarkers, proteomics and clinical translation.
• A research-oriented attitude with excellent analytical and problem-solving skills
• Ability to work in an interdisciplinary team and interested in collaborating with industrial and clinical partners.
• Experience in chromatography and mass spectrometry is preferred
• Motivated to develop your teaching skills and coach students.
• Fluent in spoken and written Dutch and/or English.

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 and application

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.

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

Information
Do you recognize yourself in this profile and would you like to know more? Please contact the hiring manager Luc Brunsveld, l.brunsveld@tue.nl.

Visit our website for more information about the application process or the conditions of employment. You can also contact HR department, hradvicebme@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 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.

PhD on data-driven inspection management and risk assessment for safety critical systems

Introduction
Are you eager to innovate risk assessment methods and reshape safety certification frameworks for safety critical systems leveraging AI and IoT technologies? This project aims at advancing inspection and data collection strategies optimization, and their integration within novel data-driven risk assessment methodologies and safety certification frameworks. We focus on vertical transport (lifts and escalators) as practical application domain: compared to the critical role that these systems play in ensuring reliable, safe, efficient and comfortable vertical transportation of people and goods, their inspection strategies, safety assessments, and certification approaches have not been updated in the era of IoT and AI. The overarching aim of this PhD research is to develop a novel data-driven safety assessment and certification framework, leveraging multiple data sources and probabilistic reliability analysis to predict both current and future safety levels. This project contributes to designing future standards and safer vertical transport.

Job Description
The availability of remote monitoring and big data opens up new opportunities to innovate traditional safety assessment and certification methods, which rely on visual inspections and reactive approaches. Future safety assessments can achieve the next level of proactiveness by collecting and analysing the right data in a timely manner, conducting data-driven probabilistic assessments of future failure risk, and optimizing inspection planning. The project will consider the application area of vertical transport (lifts and escalators). The operational data collected by the lift controller, along with records of past events, will be used to enhance the diagnostic and predictive capabilities of the safety level for the individual lift. Combining data-driven probabilistic risk assessment models and inspection planning balances cost of inspection and risk of failures, and accounts for reliability and safety. Furthermore, inspection decisions and safety assessments can be continuously updated based on new information using sequential decision-making frameworks.

Achieving such opportunities still requires creative ideas for novel methodologies based on quantitative analysis with sufficient validation. How should we collect right, timely, reliable data? How do we transfer models and data sourced from multiple, heterogeneous lifts? How do we model uncertainty and explainability of safety assessed by data and AI? How do we design appropriate certification requirements for such a safety-critical system? How do we balance cost, safety, reliability, and availability?

This project aims to find novel answers to such questions, thus developing novel safety assessment methodologies which leverage data-driven techniques and IoT technologies, and apply these to eventually support the design of future safety certification frameworks for the new generation of lifts.

The PhD candidate will design and lead the research project under the academic supervision of Prof. Claudia Fecarotti, Prof. Juseong Lee and Prof Rob Basten, and work in close collaboration with the Liftinstituut, one of the European leading certification and independent notified bodies for safety certification of lifts and escalators. You will publish the results in international journals and conferences to communicate with academia and other relevant stakeholders.

Academic and Research Environment
With this PhD project, you will conduct innovative research by becoming part of the Operations, Planning, Accounting and Control Group (OPAC) at the Department of Industrial Engineering & Innovation Science (IE&ES) at TU/e. You will be part of a challenging and diverse environment where you will interact with other PhD researchers working in the field of reliability engineering and maintenance operations, as well as other areas of operations management and industrial engineering. You will learn, apply, improve and develop modelling techniques, including data-driven methods, to support the operation of future-proof reliable vertical transport.

Job Requirements

• A master’s degree in Industrial Engineering, Mechanical Engineering, Systems Engineering, Systems and Control Engineering, (Applied) Mathematics, Engineering Mathematics, and other related fields;
• Capability and passion for working on challenging topics that have both fundamental and applied research aspects;
• Strong competence in analytical skills, mathematical skills, and quantitative modeling;
• Strong expertise in programming, including proficiency in languages commonly used in data analysis and machine learning, such as Python;
• Excellent verbal and written communication skills to collaborate in an international setting;
• Fluent in spoken and written English (C1 level);
• Ability to work in an interdisciplinary team and collaborate with industrial partners;
• Motivated to develop your teaching skills and coach students;

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 and application

About us
Eindhoven University of Technology is an internationally top-ranking Dutch university that combines scientific curiosity with a hands-on attitude. Our spirit of collaboration translates into an open culture and a number 1 position in collaborating with advanced industries. Fundamental knowledge enables us to design solutions for the highly complex problems of today and tomorrow.

Information
Do you recognize yourself in this profile and would you like to know more? Please contact Prof. Claudia Fecarotti (c.fecarotti@tue.nl), or Prof. Juseong Lee (j.lee@tue.nl).

Visit our website for more information about the application process or the conditions of employment. You can also contact HR Services (hrservices.ieis@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 by using the apply button. The application should include a:

• Cover letter (2 page max) in which you describe your motivation, research vision and qualifications for the position.
• Curriculum vitae, including a list of your publications, thesis and relevant experience.
• Contact information of two references.
• Transcripts of Master’s and Bachelor’s program, including the list of courses and grades.
• Master thesis and working papers if available.

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.

PhD on data-driven inspection management and risk assessment for safety critical systems

The availability of remote monitoring and big data opens up new opportunities to innovate traditional safety assessment and certification methods, which rely on visual inspections and reactive approaches. Future safety assessments can achieve the next level of proactiveness by collecting and analysing the right data in a timely manner, conducting data-driven probabilistic assessments of future failure risk, and optimizing inspection planning. The project will consider the application area of vertical transport (lifts and escalators). The operational data collected by the lift controller, along with records of past events, will be used to enhance the diagnostic and predictive capabilities of the safety level for the individual lift. Combining data-driven probabilistic risk assessment models and inspection planning balances cost of inspection and risk of failures, and accounts for reliability and safety. Furthermore, inspection decisions and safety assessments can be continuously updated based on new information using sequential decision-making frameworks.

Achieving such opportunities still requires creative ideas for novel methodologies based on quantitative analysis with sufficient validation. How should we collect right, timely, reliable data? How do we transfer models and data sourced from multiple, heterogeneous lifts? How do we model uncertainty and explainability of safety assessed by data and AI? How do we design appropriate certification requirements for such a safety-critical system? How do we balance cost, safety, reliability, and availability?

This project aims to find novel answers to such questions, thus developing novel safety assessment methodologies which leverage data-driven techniques and IoT technologies, and apply these to eventually support the design of future safety certification frameworks for the new generation of lifts.

The PhD candidate will design and lead the research project under the academic supervision of Prof. Claudia Fecarotti, Prof. Juseong Lee and Prof Rob Basten, and work in close collaboration with the Liftinstituut, one of the European leading certification and independent notified bodies for safety certification of lifts and escalators. You will publish the results in international journals and conferences to communicate with academia and other relevant stakeholders.

Postdoc In Identification and Control of Gravitational Wave Detectors

Short introduction
Are you excited about big science, do you have an engineering mindset, and want to contribute to the development of a new gravitational wave detector? We currently have a postdoctoral researcher opening, at the intersections of research and education, as well as systems and control and gravitational wave detection.

Job Description
The CST section has a vacancy for a postdoctoral researcher, with the aim to work on the system identification and control of critical processes in and around gravitational wave detectors. We look for candidates that either have a strong system identification and control engineering profile and are excited to work on a big science project, or have a broader background in gravitational wave detectors and are interested in developing powerful engineering tools such as identification and control methodologies. The methods will be broadly applied and consolidated in conjunction with a large number of academic institutes and SMEs, who are highly interested in adopting these techniques. As such, it provides an ideal opportunity to work at the intersection of research, education, and valorisation.

In this project, you will work closely with researchers within the Control Systems Technology section (Tom Oomen, Gert Witvoet, Koen Tiels), Nikhef (Bas Swinkels), and the ETpathfinder collaboration (Stefan Hild).

Job Requirements

• Motivated researcher, with a PhD related to either gravitational wave detectors, or system identification and control.
• Ability to conduct high quality academic research, reflected in demonstrable outputs.
• Affinity with knowledge sharing and dissemination, in particular in educational context for professionals, e.g., involving life-long learning..
• A team player who enjoys coaching 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.
• 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.

Information and application

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.

Information
Do you recognize yourself in this profile and would you like to know more? Please contact prof. dr. ir. Tom Oomen t.a.e.oomen@tue.nl, dr. ir. Gert Witvoet g.witvoet@tue.nl, or dr. ir. Koen Tiels k.tiels@tue.nl.

Visit our website for more information about the application process or the conditions of employment. You can also contact HR Services (hrservices.me@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.
• List of five self-selected ‘best publications’.

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.