Assistant Professor In Explainable Networked Systems

Karlstad University; Eindhoven; On-site; EUR 52,764 - 71,792; Full time

Benefits offered by this job

Salary in accordance with the Collective Labour Agreement for Dutch Universities

Year-end bonus of 8.3%

Annual vacation pay of 8%

Excellent technical infrastructure

High-quality training programs for academic leadership

Job summary

Karlstad University is seeking a full-time Assistant Professor for the Department of Mathematics and Computer Science in Eindhoven, Netherlands. The role involves advancing explainability techniques in networked embedded systems and contributing to educational programs in STEM.

The ideal candidate will have a PhD in Computer Science or Electrical Engineering, strong academic achievements, and motivation to teach effectively. A competitive salary and professional development opportunities are provided.

Qualifications

• At least 2-3 years of academic work experience after obtaining a PhD.
• Ability to conduct high-quality academic research reflected by publications.
• Demonstrated ability to bridge explainability methods with embedded systems.

Responsibilities

• Address challenges in explainable networked systems.
• Focus on embedded intelligence from communication protocols to interpretability.
• Contribute to the Beethoven program to educate talent in STEM fields.

Skills

Strong publication record on explainable AI

Interdisciplinary teamwork

Effective communication skills

Motivated to teach

Leadership skills

Education

PhD in Computer Science or Electrical Engineering

Job description

Job Description

You will join the Department of Mathematics and Computer Science (M&CS). With over 140 (assistant, associate and full) professors, almost 250 PhD and EngD students, nearly 3000 students, M&CS is the largest department of the TU/e. By performing top‑level fundamental and applied research, and maintaining strong ties with industry, M&CS aims to contribute to science and innovation in and beyond the region.

The Interconnected Resource‑aware Intelligent Systems (IRIS) cluster within this department is looking for a full‑time assistant professor, who will address the challenges related to the design, development and maintenance of the next generation of explainable, transparent, and trustworthy networked embedded systems.

Explainable networked (embedded) systems such as autonomous vehicles, smart energy infrastructures and industrial IoT platforms increasingly make autonomous or semi‑autonomous decisions. Understanding why a system behaves in a certain way becomes critical for safety, certification, debugging and user acceptance. Explainability ensures that complex interactions between distributed components remain interpretable, enabling engineers to trace decisions, identify anomalies, control quality, and design systems that behave reliably even under uncertainty.

As an assistant professor you will focus on advancing techniques that make embedded intelligence understandable, from communication protocols that preserve contextual information to algorithms capable of producing human‑interpretable outputs. You will explore explainability across embedded network–software boundaries, ensuring that distributed components, sensing/actuation pipelines and decision‑making algorithms remain transparent and traceable.

IRIS research is performed in the context of various application domains including automotive, smart industry, predictive maintenance, logistics, smart cities, health and wellbeing, and intelligent lighting. The industrial applications and collaborations inspire IRIS in its research and ensure that its research outcomes remain as close as possible to real‑world problems and have economic and societal impacts.

In this role you will contribute to the ambition of the Beethoven program to educate top talent and strengthen research across the fields of Science, Technology, Engineering and Mathematics (STEM).

Job Requirements

• Motivated researcher with a PhD in Computer Science or Electrical Engineering, a strong publication record on the conjunction of explainable AI and networked (embedded) systems, outstanding research achievements, and indicators of international recognition such as invited talks and service on PC, TPC, and/or editorial boards.
• At least 2–3 years of academic work experience after obtaining a PhD.
• Ability to conduct high‑quality academic research, reflected by publications in top venues.
• Demonstrated ability to bridge explainability methods with networked (embedded) systems.
• Motivated to teach, contribute to teaching processes, and develop excellent teaching skills.
• Strong cooperation skills and ability to work in an interdisciplinary team.
• Effective communication and leadership skills, including coaching and mentoring students and leading a project.
• Excellent written and verbal proficiency in English.

Conditions of Employment

• Salary in accordance with the Collective Labour Agreement for Dutch Universities. For an Assistant Professor this is (scale 11) €4,728 – €6,433 gross per month (full‑time).
• A year‑end bonus of 8.3% and annual vacation pay of 8%.
• A dedicated mentoring program to help you get to know the university and the Dutch research environment.
• Development Track with the prospect of becoming an Associate Professor; if you have a more senior profile, a tailor‑made career proposal will be considered.
• High‑quality training programs for academic leadership and teaching.
• 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 allowance for commuting, working from home and internet costs.
• Staff Immigration Team available for international candidates, a tax compensation scheme (30% facility) and partner career support.

Application

• Cover letter describing your motivation and qualifications for the position.
• Curriculum vitae, including a list of your publications and the contact information of three references. The university may contact references at any stage of the recruitment process.
• Description of your scientific interests and plans (1–2 pages).
• Statement of your teaching goals and experience (1–2 pages).

All requested documents must be submitted. Incomplete applications may not be considered and could be rejected. The deadline for applications is September 15, 2026.

The recruitment process will include the following sequential selection rounds:

• Online interviews with the selection committee.
• Candidates’ day on campus, including interviews and an introduction program to the group, department and university.

Applications will be reviewed once the vacancy has closed.

Please note

• You can apply online only; applications sent by email or post will not be processed.
• A pre‑employment screening (e.g., knowledge security check) may be part of the selection procedure. For more information, consult the National Knowledge Security Guidelines.
• Please do not contact us for unsolicited services.