PhD on Multi-Faceted Visual Process Analytics

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

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

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

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

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

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

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

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

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

Conditions of Employment
A meaningful job in a dynamic and ambitious university, in an interdisciplinary setting and within an international network. You will work on a beautiful, green campus within walking distance of the central train station. In addition, we offer you:

• Full-time employment for four years, with an intermediate assessment after nine months. You will spend a minimum of 10% of your four-year employment on teaching tasks, with a maximum of 15% per year of your employment.
• Salary and benefits (such as a pension scheme, paid pregnancy and maternity leave, partially paid parental leave) in accordance with the Collective Labour Agreement for Dutch Universities, scale P (min. € 3,059 - max. € 3,881).
• A year-end bonus of 8.3% and annual vacation pay of 8%.
• High-quality training programs and other support to grow into a self-aware, autonomous scientific researcher. At TU/e we challenge you to take charge of your own learning process.
• An excellent technical infrastructure, on-campus children's day care and sports facilities.
• An allowance for commuting, working from home and internet costs.
• A Staff Immigration Team and a tax compensation scheme (the 30% facility) for international candidates.

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

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

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

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

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

• Cover letter in which you describe your motivation and qualifications for the position.
• Curriculum vitae, including a list of your publications and the contact information of three references.

We look forward to receiving your application and will screen it as soon as possible. The vacancy will remain open until the position is filled.

Please note

• You can apply online. We will not process applications sent by email and/or post.
• A pre-employment screening (e.g. knowledge security check) can be part of the selection procedure. For more information on the knowledge security check, please consult Chapter 8 of the National Knowledge Security Guidelines.
• Please do not contact us for unsolicited services.

PhD on Multi-Faceted Visual Process Analytics

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

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

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

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

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

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

Senior Data Solutions Engineer

Join the Data Revolution at TU/e: Where Data Meets Discovery! As the data team for researchers, we empower our community with tailored and cost-effective data solutions for pioneering innovations. As part of the Product Area Research (PAR), our mission is to equip our university’s brightest minds with the tools and technology they need to navigate the entire research data & AI lifecycle. We are building an advanced data ecosystem that’s more than just infrastructure, it’s a launchpad for groundbreaking investigations. Technology evolves fast and so do we. While continuously reinventing ourselves, we take pride in putting strong foundations first.

Together with our research community across TU/e, we explore and validate new ways of working with data. This ranges from testing and integrating techniques such as synthetic data to developing the smart campus data ecosystem, where we provide the infrastructure building blocks that turn real campus data into shared foundations for advanced analytics and data-driven decision-making at TU/e. That is why we are looking for a Senior Data Solutions Engineer to join us on this journey.

Your role
This is more than a technical position. It is an opportunity to play a strategic role in shaping the future of research data services at TU/e and to contribute directly to innovations that support our researchers and the wider university community.

As our Senior Data Solutions Engineer, you will work closely with the Tech Lead as a senior technical counterpart within a small, ambitious team consisting of three developers and a Product Owner. Together, you will help guide the next phase of growth for the platform as we move from foundational delivery towards a mature, scalable, and high-performing engineering organisation.

We believe modern data engineering is no longer limited to pipelines and storage alone. It is increasingly about connecting systems, enabling users, automating intelligently, and creating solutions that are both efficient and sustainable. New development practices, including AI-assisted engineering tools, offer opportunities to accelerate routine work and allow greater focus on architecture, security, maintainability, and user experience.

If you are motivated by building modern data platforms, experimenting with new approaches, and delivering solutions that create real impact in a dynamic academic environment, get in touch!

What you will do
You will work in lockstep with the Tech Lead to shape our technical roadmap. We are looking for a disciplined engineer who can navigate the "big picture" while ensuring our infrastructure remains rock-solid; someone who turns complex ideas into production-worthy reality with independent initiative.

• You will work across multiple layers of the platform, contributing where needed—from infrastructure automation and backend engineering to user-facing tools and integrations.
• You will rapidly prototype new solutions where appropriate, while applying the necessary care and governance when working with production systems, security-sensitive environments, and institutional data.
• You will design and implement integrations between data platforms, APIs, databases, and emerging AI capabilities to create coherent and scalable solutions for researchers.
• You will use modern development tooling, including AI-assisted engineering tools, to improve productivity while maintaining quality and reliability standards.
• You will prototype and develop practical researcher-facing solutions, using appropriate technologies such as APIs, modern web frameworks, and AI-assisted development tooling.

Senior Data Solutions Engineer

Job Description
Join the Data Revolution at TU/e: Where Data Meets Discovery! As the data team for researchers, we empower our community with tailored and cost-effective data solutions for pioneering innovations. As part of the Product Area Research (PAR), our mission is to equip our university’s brightest minds with the tools and technology they need to navigate the entire research data & AI lifecycle. We are building an advanced data ecosystem that’s more than just infrastructure, it’s a launchpad for groundbreaking investigations. Technology evolves fast and so do we. While continuously reinventing ourselves, we take pride in putting strong foundations first.

Together with our research community across TU/e, we explore and validate new ways of working with data. This ranges from testing and integrating techniques such as synthetic data to developing the smart campus data ecosystem, where we provide the infrastructure building blocks that turn real campus data into shared foundations for advanced analytics and data-driven decision-making at TU/e. That is why we are looking for a Senior Data Solutions Engineer to join us on this journey.

Your role
This is more than a technical position. It is an opportunity to play a strategic role in shaping the future of research data services at TU/e and to contribute directly to innovations that support our researchers and the wider university community.

As our Senior Data Solutions Engineer, you will work closely with the Tech Lead as a senior technical counterpart within a small, ambitious team consisting of three developers and a Product Owner. Together, you will help guide the next phase of growth for the platform as we move from foundational delivery towards a mature, scalable, and high-performing engineering organisation.

We believe modern data engineering is no longer limited to pipelines and storage alone. It is increasingly about connecting systems, enabling users, automating intelligently, and creating solutions that are both efficient and sustainable. New development practices, including AI-assisted engineering tools, offer opportunities to accelerate routine work and allow greater focus on architecture, security, maintainability, and user experience.

If you are motivated by building modern data platforms, experimenting with new approaches, and delivering solutions that create real impact in a dynamic academic environment, get in touch!

What you will do
You will work in lockstep with the Tech Lead to shape our technical roadmap. We are looking for a disciplined engineer who can navigate the "big picture" while ensuring our infrastructure remains rock-solid; someone who turns complex ideas into production-worthy reality with independent initiative.

• You will work across multiple layers of the platform, contributing where needed—from infrastructure automation and backend engineering to user-facing tools and integrations.
• You will rapidly prototype new solutions where appropriate, while applying the necessary care and governance when working with production systems, security-sensitive environments, and institutional data.
• You will design and implement integrations between data platforms, APIs, databases, and emerging AI capabilities to create coherent and scalable solutions for researchers.
• You will use modern development tooling, including AI-assisted engineering tools, to improve productivity while maintaining quality and reliability standards.
• You will prototype and develop practical researcher-facing solutions, using appropriate technologies such as APIs, modern web frameworks, and AI-assisted development tooling.

Job Requirements
What you bring

• You have a strong background in software and data engineering, with demonstrable experience in building and maintaining reliable production environments.
• You have extensive experience with Python, Apache Spark, and Databricks, including the development and management of data pipelines and platform components.
• You have experience with Terraform and infrastructure-as-code principles, preferably combined with Databricks Asset Bundles or similar deployment tooling.
• You have experience with Azure services or comparable cloud platforms, and a solid understanding of infrastructure concepts such as networking, security, storage, containers, and virtual environments.
• You are familiar with networking concepts such as VNets, subnets, private connectivity, NAT gateways, and firewalls.
• You have a pragmatic and solution-oriented mindset, are able to work independently, communicate effectively with different stakeholders, and are interested in developments such as event-driven architectures and AI-supported engineering practices.
• You understand how AI-assisted engineering can improve productivity and apply these tools with sound judgment, enabling greater focus on architecture, security, maintainability, and user experience.

Conditions of Employment
An exciting position within an international yet personal university. You are right in the middle of the students, on a green campus within walking distance of the central station. Besides beautiful architecture, you will find varied workplaces and excellent sports facilities. We also offer you:

• A monthly salary of minimum € 3.546,- to maximum € 6.433,- for full-time employment, depending on your knowledge and experience (scale 10/11 Collective Labour Agreement for Dutch Universities).
• In addition to vacation pay, a structural end-of-year bonus of 8.3%.
• A favorable arrangement for more holidays or a sabbatical.
• A selection model for additional fringe benefits.
• Working hours in consultation for an optimal work-life balance.
• Scope for your talent with advancement prospects and excellent development opportunities such as mentoring, workshops and coaching.
• Partially paid parental leave and reimbursement for commuting expenses, working from home and the internet.
• A generous employer contribution to the favorable ABP pension plan.
• Unlimited access to the modern on‑campus TU/e Student Sports Center at an exceptionally affordable rate.

Here 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 have more information about the position, please contact the hiring manager: Oana Candel, Product Owner, i.a.candel@tue.nl.

Visit our website for more information about the application process. You can also contact Rob van der Linden, Senior Recruiter, r.m.e.v.d.linden@tue.nl.

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

Application
If you are interested, please use the ‘apply’ button to send us your CV and letter of application with your motivation and a description of your qualifications. Ensure that you submit all the requested application documents. We give priority to complete applications.

Screening of candidates begins as soon as applications are received and continues until the position is filled. Where applicable, internal candidates will be given priority over external candidates where they are equally suitable.

We look forward to receiving your application!

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.
• Important for non-EU applicants: Please be aware that for this position, specific residence permit requirements apply. If you are a non-EU national, you may not be eligible to legally work in this role under current Dutch immigration regulations. We strongly advise you to contact our Staff Immigration Team (staffimmigration@tue.nl) before applying to check your eligibility and to receive further guidance.
• Please do not contact us for unsolicited services.

Business Controller

Introductie
Ben jij een ervaren controller die wil optreden als strategisch business partner voor het bestuur en management van de faculteit Biomedical Engineering van de Technische Universiteit Eindhoven (TU/e)? Werk je graag in een dynamische, innovatieve omgeving waar wetenschap, technologie en complexe financiële vraagstukken samenkomen? Lees dan verder of solliciteer direct!

Functieomschrijving
Als Business Controller ben je de strategische partner van de faculteit Biomedical Engineering. Je opereert op het snijvlak van strategie, prestaties en financiën en ondersteunt het faculteitsbestuur en management bij het nemen van goed onderbouwde beslissingen. Je verbindt financiële en niet‑financiële informatie en vertaalt strategische ambities naar concrete keuzes, prioriteiten en stuurinformatie.

Je bent verantwoordelijk voor een solide Planning & Control‑cyclus en helpt de faculteit om tijdig inzicht te krijgen in prestaties, kansen en risico’s. Je kijkt nadrukkelijk vooruit, ontwikkelt scenario’s en ondersteunt bij het maken van strategische en financiële afwegingen in een complexe en dynamische omgeving.

In deze rol fungeer je als kritische sparringpartner voor bestuur en management. Je stelt verdiepende vragen, maakt impliciete aannames expliciet en helpt bij het structureren van besluitvorming. Daarnaast werk je nauw samen met collega’s binnen Finance & Control en andere ondersteunende diensten om processen te verbeteren en de organisatie verder te professionaliseren.

Wat ga je doen?

• Optreden als strategisch en financieel sparringpartner voor het faculteitsbestuur en management.
• Ondersteunen bij het formuleren en vertalen van strategische doelstellingen naar concrete plannen en financiële kaders.
• Verantwoordelijk voor de inrichting en uitvoering van de Planning & Control‑cyclus.
• Ontwikkelen van managementinformatie, KPI’s en analyses ter ondersteuning van besluitvorming.
• Uitvoeren van scenario‑analyses en meerjarenprognoses om strategische keuzes te onderbouwen.
• Initiëren, begeleiden en toetsen van business cases en investeringsvoorstellen.
• Inzichtelijk maken en bespreken van financiële, strategische en operationele risico’s.
• Samenwerken met andere disciplines binnen de TU/e en bijdragen aan TU/e‑brede verbeterinitiatieven binnen Finance & Control.

Functie-eisen

• Je bent een stevige business partner met strategisch inzicht en een analytische blik.
• Je bent in staat om complexe vraagstukken te vertalen naar heldere inzichten en adviezen.
• Je beschikt over sterke communicatieve vaardigheden en weet stakeholders op verschillende niveaus mee te nemen in jouw analyses en adviezen.
• Je hebt organisatiesensitiviteit en kunt effectief opereren in een bestuurlijke en dynamische omgeving.
• Je hebt een relevante financiële opleiding op HBO+ of WO‑niveau.
• Je hebt meerdere jaren relevante ervaring binnen finance, control of business control.

Affiniteit met hoger onderwijs, onderzoek of complexe organisaties beschouwen we als een pré.

Arbeidsvoorwaarden
Een boeiende positie binnen een internationale en tegelijkertijd persoonlijke universiteit. Je zit midden tussen de studenten, op een groene campus op loopafstand van het centraal station. Daarnaast bieden we jou:

• Een maandsalaris van minimaal € 4.728,- tot maximaal € 7.297,- bij een fulltime dienstverband, afhankelijk van jouw kennis en ervaring (schaal 11/12 cao Nederlandse Universiteiten).
• Naast vakantiegeld, een structurele eindejaarsuitkering van 8,3%.
• Een gunstige regeling voor extra verlofdagen of een sabbatical.
• Een keuzemodel voor extra secundaire arbeidsvoorwaarden.
• Werktijden in overleg voor een optimale werk-privé balans.
• Ruimte voor jouw talent met doorgroeikansen en uitstekende ontwikkelmogelijkheden, zoals mentoring, workshops en coaching.
• Deels betaald ouderschapsverlof en een vergoeding voor reiskosten woon-werkverkeer, thuiswerken en internet.
• Een ruime werkgeversbijdrage aan de gunstige ABP-pensioenregeling.
• Toegang tot het moderne sportcentrum op de TU/e‑campus tegen een uitzonderlijk voordelig tarief.

Hier ontdek je nog meer informatie over onze arbeidsvoorwaarden. Bouw verder aan je carrière bij de TU/e!

Over ons
Wij zijn een toonaangevende internationale universiteit waar wetenschappelijke nieuwsgierigheid samenkomt met een pragmatische, hands‑on mentaliteit. We werken op een open en samenwerkingsgerichte manier met hightechindustrieën om complexe maatschappelijke uitdagingen aan te pakken. Onze verantwoordelijke en respectvolle benadering zorgt voor impact — vandaag én in de toekomst. TU/e is de thuisbasis van meer dan 13.000 studenten en ruim 7.000 medewerkers, samen een diverse en bruisende academische gemeenschap.

Onze universiteit bevindt zich in Brainport Eindhoven — een wereldwijd toonaangevende technologieregio met meer dan 7.000 hightechbedrijven en sterke R&D‑activiteiten. Brainport staat bekend om doorbraken op het gebied van AI, fotonica, halfgeleiders en geavanceerde maakindustrie. Het is een regio waar technologie in dienst staat van mensen en de samenleving. Meer informatie over de Brainport‑regio vind je hier.

Informatie
Wil je meer informatie over deze functie? Neem dan contact op met Maurice van Eijsden, Manager Business Control & Reporting. E-mail: m.p.m.v.eijsden@tue.nl of +31 (0)40 247 8163.

Informatie over de arbeidsvoorwaarden vind je hier en voor overige vragen kun je contact opnemen met TU/e Recruiter Rob van der via Linden, via r.m.e.v.d.linden@tue.nl of via 06-39582273.

Nieuwsgierig geworden? Op www.tue.nl/jobs vind je meer over werken bij de TU/e.

Sollicitatie
Ben je geïnteresseerd? Via de solliciteerknop ontvangen we graag je CV en brief met motivatie en omschrijving van je kwalificaties. Zorg ervoor dat je alle gevraagde documenten toevoegt. Wij geven voorrang aan complete sollicitaties.

De screening van kandidaten begint zodra de sollicitaties zijn ontvangen en gaat door totdat de vacature is ingevuld. Indien van toepassing, krijgen interne kandidaten bij gelijke geschiktheid voorrang op externe kandidaten.

We kijken uit naar je sollicitatie!

Let op

• Je kunt online solliciteren. Sollicitaties die per e-mail en/of post worden verstuurd, worden niet in behandeling genomen.
• Een voorafgaande screening (bijvoorbeeld een Verklaring omtrent Gedrag of kennisveiligheidscheck) kan onderdeel zijn van de selectieprocedure. Voor meer informatie over de kennisveiligheidscheck, raadpleeg de Nationale Richtlijnen Kennisveiligheid.
• Wij verzoeken je geen contact met ons op te nemen voor ongevraagde diensten.