PhD in Adaptive AI Defense: Reinforcement Learning for Cybersecurity

Are you fascinated by how machine learning—especially reinforcement learning—can transform the way we secure modern computer networks? Do you want to work on approaches that adapt to new threats while accounting for real-world user behavior? Then join us!

Today’s networks face increasing complexity and sophisticated cyberattacks. At the same time, legitimate users demand easy access with minimal disruption. Balancing these competing needs requires dynamic defense strategies that can learn and evolve over time. In this project, you will help design and analyze reinforcement learning methods—potentially involving multiple interacting agents—to defend computing systems. This may involve modelling defender, adversary, and user agents, all of whom have their own objectives within the system. Ultimately, your work will advance both the theoretical foundations of RL-based cybersecurity and its practical implementation for modern networks.

Job Description
We are looking for a motivated and talented PhD student with a passion for reinforcement learning and cybersecurity. Your main objectives will be to contribute to realistic cybersecurity benchmarks and simulators for the RL research community, develop state-of-the-art algorithms that adapt to changing threats, incorporate user models, and provide tangible performance assurance. You will investigate how to represent network environments, implement multi-agent or single-agent RL approaches, and evaluate them using realistic scenarios. Your research may have a direct real societal impact by helping to protect critical infrastructure and everyday technology users.

Your responsibilities will include:

• Conducting independent and collaborative research on reinforcement learning for cybersecurity.
• Proposing and validating algorithms that consider adversarial threats, user behavior, and dynamic network conditions.
• Publishing findings in top-tier conferences and journals.
• Assisting with educational tasks such as tutorials and student supervision.

Requirements

• M.Sc. degree (completed or near completion) in Computer Science, Cyber Security, Artificial Intelligence, or a related field.
• Demonstrated interest and experience (e.g., via projects, code, or publications) in reinforcement learning and/or cybersecurity.
• Experience with programming (e.g., in Python, C/C++, or similar)
• Proficiency in English (oral and written).
• Excellent communication and collaboration skills.

Additionally, it would be a plus if you have familiarity with machine learning or data-driven approaches.

If your profile doesn’t perfectly match the above criteria but you’re enthusiastic about this project, we would still love to hear from you. We value diverse perspectives and welcome applicants from a variety of backgrounds.

What we offer
As PhD in Adaptive AI Defense: Reinforcement Learning for Cybersecurity at Faculty of Science & Engineering, you will be employed by the most international university in the Netherlands, located in the beautiful city of Maastricht. In addition, we offer you:

• Good employment conditions. The position is graded in scale P according to UFO profile PhD, with corresponding salary based on experience ranging from €2901,00 and €3707,00 gross per month (based on a full-time employment of 38 hours per week). In addition to the monthly salary, an 8.0% holiday allowance and an 8.3% year-end bonus apply.
• An employment contract for a period of 12 months with a scope of 1,0 FTE. Upon a positive evaluation, an extension of 3 years will follow.
• At Maastricht University, the well-being of our employees is of utmost importance, we offer flexible working hours and the possibility to work partly from home if the nature of your position allows it. You will receive a monthly commuting and internet allowance for this. If you work full-time, you will be entitled to 29 vacation days and 4 additional public holidays per year, namely carnival Monday, carnival Tuesday, Good Friday, and Liberation Day. If you choose to accumulate compensation hours, an additional 12 days will be added. Furthermore, you can personalize your employment conditions through a collective labor agreement (CAO) choice model.
• As Maastricht University, we offer various other excellent secondary employment conditions. These include a good pension scheme with the ABP and the opportunity for UM employees to participate in company fitness and make use of the extensive sports facilities that we also offer to our students.
• Last but certainly not least, we provide the space and facilities for your personal and professional development. We facilitate this by offering a wide range of training programs and supporting various well-established initiatives such as 'acknowledge and appreciate'.

The terms of employment at Maastricht University are largely set out in the collective labor agreement of Dutch Universities. In addition, local provisions specific to UM apply. For more information, click here.

Maastricht University
Why work at Maastricht University?

At Maastricht University (UM), everything revolves around the future. The future of our students, as we work to equip them with a solid, broad-based foundation for the rest of their lives. And the future of society, as we seek solutions through our research to issues from all around the world. Our six faculties combined provide a comprehensive package of study programmes and research.

In our teaching, we use the Problem-Based Learning (PBL) method. Students work in small groups, looking for solutions to problems themselves. By discussing issues and working together to draw conclusions, formulate answers and present them to their peers, students develop essential skills for their future careers.

With over 22,300 students and more than 5,000 employees from all over the world, UM is home to a vibrant and inspiring international community.

Are you drawn to an international setting focused on education, science and scholarship? Are you keen to contribute however your skills and qualities allow? Our door is open to you! As a young European university, we value your talent and look forward to creating the future together.

Click here for more information about UM.

Faculty of Science and Engineering
At the Faculty of Science and Engineering (FSE), we focus on themes such as circularity and sustainability, future farming, digitisation and (scientific) instrument development. FSE's leading projects, like the Einstein Telescope Pathfinder, are sure to grab anyone's attention. The faculty is a vibrant hub of education and research in Science, Technology, Engineering, and Mathematics (STEM) and Liberal Arts and Sciences (LAS). At FSE, over 450 staff members and 3700 students gather to explore e exciting interdisciplinary research and educational programmes. Feel welcome, be part of our team and put your brilliant mind to work!

FSE at the Brightlands Campuses
Maastricht, Sittard-Geleen, Heerlen, and Venlo, the home of four creative Brightlands campuses, are bustling with 30,000 entrepreneurs, researchers, and students working diligently to solve global challenges. The Faculty of Science and Engineering is active on all four Brightlands campuses, and this is where our impact reaches its peak. To give you an idea of what is happening at each campus: Sittard-Geleen is home to the largest chemical site in the Euregion, while Venlo is a large hub for agri-food innovation. Maastricht is the site of the Health Campus, and Heerlen is the place to be for Smart Services.

Department of Advanced Computing Sciences
The Department of Advanced Computing Sciences is Maastricht University’s largest and oldest department broadly covering the fields of artificial intelligence, data science, computer science, mathematics and robotics.
Over 100 researchers work and study in the Department of Advanced Computing Sciences, whose roots trace back to 1987. The department’s staff teaches approximately 1250 bachelor’s and master’s students in 4 specialized study programmes in Data Science and Artificial Intelligence. Click here for more information.

Curious?
Are you interested in this exciting position but still have questions? Feel free to contact Dr. Ashish Sai at ashish.sai@maastrichtuniversity.nl or Dr. Dennis Soemers at dennis.soemers@maastrichtuniversity.nl.

Applying?
Or are you already convinced and ready to become our new PhD Candidate? Apply now, no later than May 11, 2025, for this position.

To apply for the position, submit the following documents:

• cover letter (1 page max), which includes a motivation of your interest in the vacancy and an explanation of why you would fit well for the PhD position;
• a detailed curriculum vitae;
• a course list of your Masters and Bachelor programs (including grades);
• results of a recent English language test, or other evidence of your English language capabilities;
• name and contact information of two references

The vacancy is open for internal and external candidates. In case of equal qualifications, internal candidates will be prioritized.

Maastricht University is committed to promoting and nurturing a diverse and inclusive community. We believe that diversity in our staff and student population contributes to the quality of research and education at UM, and strive to enable this through inclusive policies and innovative projects led by teams of staff and students. We encourage you to apply for this position.

38 hours per week

Paul-Henri Spaaklaan 1