Senior Accountant

• Verantwoordelijk voor de volledige accounting, inclusief maandafsluitingen, boekingen en rekeningafstemmingen.
• Opstellen en analyseren van financiële rapporteringen voor zowel interne als externe stakeholders.
• Waarborgen van een correcte financiële verwerking volgens de correcte richtlijnen en interne procedures.
• Onderhouden en versterken van interne controles ter garantie van de kwaliteit en betrouwbaarheid van financiële gegevens.
• Ondersteunen van fiscale rapporteringen, analyses en externe audits.
• Uitvoeren van financiële analyses, bijdragen aan projecten en identificeren van proces- en efficiëntieverbeteringen in samenwerking met operationele teams.

Dossierbeheerder Accountancy | Warme omgeving, Sterke dossiers & korte Lijnen | Roeselare

Als dossierbeheerder beheer je een eigen klantenportefeuille en ben je een belangrijke schakel tussen ondernemer en kantoor. Je krijgt het vertrouwen om jouw dossiers zelfstandig op te volgen en uit te bouwen tot duurzame klantenrelaties.

Jouw verantwoordelijkheden bestaan onder andere uit:

• Beheren van dossiers van A tot Z voor vennootschappen en zelfstandigen
• Opmaken en indienen van btw-aangiftes, personen- en vennootschapsbelasting
• Voorbereiden van tussentijdse resultaten en jaarafsluitingen
• Adviseren en begeleiden van klanten bij financiële en fiscale vraagstukken
• Signaleren van optimalisaties en opportuniteiten binnen jouw dossiers

Je komt terecht in een omgeving waar initiatief gewaardeerd wordt en waar je de ruimte krijgt om jouw expertise verder uit te bouwen.

PhD in Computer Architecture for Real-Time AI at the Edge

Introduction
Join the NWO Perspectief FIND program and help design next-generation computer architectures for running large AI models on embedded and edge systems under strict timing, energy, and memory constraints. You’ll explore hardware-aware optimization and co-design with accelerators (FPGAs, GPUs, near-memory systems) to achieve real-time, energy-efficient AI for high-tech industry applications. Work with leading companies like ASMPT and shape the future of AI at the edge!

Job Description
Industrial edge deployments—in semiconductor manufacturing, printing systems, automotive radar, smart mobility cameras, and HealthTech—require on-device AI to ensure low latency, privacy, and resilience. Today’s Transformers models scale poorly and assume abundant cloud resources. The research program FIND aims to deliver architectural and algorithmic breakthroughs that enable foundation models to run predictably and efficiently on embedded processors and accelerators.

FIND is a research program funded by the Dutch government and industry that brings together 5 universities, 11 companies (startups to multinationals), and 2 knowledge institutes to develop foundation models (large AI models) for Dutch high‑tech industry, with strong emphasis on edge deployment, privacy, and timely decision‑making. Partners include ASML, NXP, Canon, ASMPT, Technolution, Signify, Shell, Stryker, TNO, and others. A total of 12 PhDs will be employed on the FIND program covering topics from foundation model pre-training and multimodal adaptation to architectures and compression for edge deployment while targeting real-world validation in domains like HealthTech, smart industry, and autonomous mobility.

This PhD position focuses on the design of novel computer architectures to enable large AI models to run on embedded and edge systems under strict timing, energy, and memory constraints. Current solutions typically rely on general-purpose CPUs or GPUs, which are optimized for flexibility rather than predictable real-time performance. These platforms struggle with the complexity and resource demands of foundation models, leading to high latency, excessive energy consumption, and large memory footprints—making them unsuitable for safety-critical or resource-constrained environments.

In addition, you will explore model compression and co-optimization with hardware accelerators. Unlike existing approaches that apply compression techniques (e.g., pruning, quantization) in isolation, this research will jointly optimize algorithms and hardware. Co-optimization ensures that architectural decisions—such as token merging, sparsity exploitation, and quantization—are aligned with hardware datapaths and memory hierarchies. This enables predictable real-time performance, energy efficiency, and scalability across heterogeneous platforms (embedded CPUs, GPUs, FPGAs, near-memory accelerators). The result is a shift from “best-effort” execution on generic hardware to deterministic, deadline-compliant AI inference tailored for industrial edge systems.

These architectures and accelerators will be prototyped and validated in collaboration with a leading high-tech semiconductor manufacturing company, demonstrating how edge devices can execute foundation models with guaranteed performance and minimal energy footprint—closing the gap between AI capability and embedded system constraints.

Research group and company
This position is embedded in the Electronic Systems (ES) group within the Electrical Engineering department at Eindhoven University of Technology (TU/e). Our group consists of six full professors, three associate professors, seven assistant professors, several postdocs, approximately 40 EngD and PhD candidates, and support staff. The ES group is world-renowned for its design automation and embedded systems research.

This PhD project is executed in close collaboration with ASMPT which is the only company in the world offering a comprehensive portfolio of integrated solutions for all major steps in electronics manufacturing – from carrier for chip interconnection to chip assembly and packaging to SMT.

Job Requirements

• A master’s degree (or an equivalent university degree) in Computer Engineering, Electrical Engineering, Embedded Systems, or related background and strong hardware design skills.
• Strong background in computer architecture, digital design, and real-time systems. Knowledge of embedded systems and hardware/software co-design.
• Experience with hardware acceleration (FPGAs, GPUs, SoCs) and low-power design.
• Familiarity with deep learning frameworks (e.g., PyTorch, TensorFlow) is a plus.
• 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? Please contact the hiring manager dr.ir. Sander Stuijk, s.stuijk@tue.nl.

Visit our website for more information about the application process. You can also contact Kevin Caris, HR advisor, k.t.caris@tue.nl or +31 40 247 8835.

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

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

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

• Cover letter in which you describe your motivation and qualifications for the position.
• Curriculum vitae, including a list of your publications and the contact information of three references. Kindly note that we may reach out to references at any stage of the recruitment process. We recommend notifying your references upon submitting your application.

Ensure that you submit all the requested application documents. We give priority to complete applications.

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

Please note

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

Postdoc Behaviour-Aware Dispatch and Cycling Safety in Urban Logistics

Job description

Platform-mediated cycling logistics has become a structural component of urban freight in the Netherlands, yet the coordination between platform operations and municipal safety planning remains underdeveloped. The PROSPER project, funded under TKI Dinalog, develops decision-support methods to inform this coordination, in collaboration with platform, municipal, and academic partners. The postdoctoral position offered here constitutes the methodological core of the project.

The work combines empirical analysis of courier movement data, spatial modelling of urban risk exposure, and simulation-based evaluation of routing and policy strategies. The successful candidate will lead the technical research, contribute to publications in leading journals in transportation and operations research, and help shape the translation of the resulting methods into outputs developed with the project's industrial and municipal partners.

The position is hosted by the ORBIT Lab (Operations Research and Behavioural Informatics in Transportation) at the Faculty of Technology, Policy and Management, under the supervision of Dr. Yousef Maknoon.

Job requirements

• A PhD in operations research, transportation, applied mathematics, computer science, or a closely related quantitative field.
• Strong research background in mathematical optimisation, simulation, or behavioural modelling for mobility or logistics.
• Fluent in Python, comfortable with geospatial data and large movement datasets.
• First-author publications in international peer-reviewed journals.
• Able to communicate technical results clearly to industrial and municipal partners.

Valued:

• Prior work on routing, dispatch, or last-mile logistics.
• Experience with discrete choice or stated-preference modelling.
• Familiarity with cycling safety or platform-mediated work.
• Track record of turning research into working tools.

TU Delft (Delft University of Technology)
Delft University of Technology is built on strong foundations. As creators of the world-famous Dutch waterworks and pioneers in biotech, TU Delft is a top international university combining science, engineering and design. It delivers world class results in education, research and innovation to address challenges in the areas of energy, climate, mobility, health and digital society. For generations, our engineers have proven to be entrepreneurial problem-solvers, both in business and in a social context.

At TU Delft we embrace diversity as one of our core values and we actively engage to be a university where you feel at home and can flourish. We value different perspectives and qualities. We believe this makes our work more innovative, the TU Delft community more vibrant and the world more just. Together, we imagine, invent and create solutions using technology to have a positive impact on a global scale. That is why we invite you to apply. Your application will receive fair consideration.

Challenge. Change. Impact!

Faculty Technology, Policy and Management
The Faculty of TPM provides an important contribution to solving complex technical-social issues, such as energy transition, mobility, digitalisation, water management and (cyber) security. TPM does this with its excellent education and research at the intersection of technology, society and policy. We combine insights from both engineering and social sciences as well as the humanities. TPM develops robust models and designs, is internationally oriented and has an extensive network of knowledge institutions, companies, social organisations and governments.

Click here to go to the website of the Faculty of Technology, Policy and Management.

Lerarenopleider vakdidactiek Duits

Als lerarenopleider vakdidactiek Duits lever je een belangrijke bijdrage aan het opleiden van docenten in het voortgezet onderwijs die zich onderscheiden door een grondige en actuele kennis van het wetenschappelijke onderzoek in hun vakgebied. Dankzij jouw ervaringen ontwikkel, ontwerp, verzorg en evalueer je samen met collega’s, (vak)didactische onderdelen van de opleidingen tot eerstegraads leraar en heb jij hier een duidelijke visie op.

Daarnaast ben je inzetbaar voor onderwijs gericht op generieke competenties van leraren, zoals persoonlijke professionele ontwikkeling. Je onderhoudt contacten met de vakbegeleiders in de stagescholen en verzorgt samen met de Radboud Docenten Academie professionaliseringsactiviteiten voor het schoolvak. In deze rol draag je actief bij aan onderwijsinnovatie en aan een veilig en inclusief werkklimaat.