PhD on Algorithmic Fairness for Data-Driven Decision Making

Are you interested in ethical AI and eager to develop solutions that address the challenges of biased decision-making in machine learning (ML)? This PhD position offers a unique opportunity to contribute to cutting-edge research in algorithmic fairness, ensuring that automated decision-making systems produce equitable and unbiased outcomes.

Project Description

Machine learning algorithms increasingly influence high-stakes decisions in society—shaping energy pricing, university admissions, loan approvals, and more. While these systems can enhance efficiency, they often inherit and amplify societal biases, leading to serious ethical, legal, and social concerns.

In practice, the automated decisions can have dynamic feedback effects on the system itself which can perpetuate over time.  For example, ML-driven energy pricing models adjust costs based on demand, supply, and user behavior. However, these mechanisms may unintentionally disadvantage vulnerable communities by charging higher rates during peak hours, thereby reinforcing existing disparities in energy access. To counteract such effects, tools from optimal control, distributed control, and optimization can be leveraged to enforce fairness constraints, ensuring that efficiency and cost-effectiveness are balanced with equity. Despite recent efforts to mitigate bias, there remains a fundamental gap in understanding the long-term feedback dynamics of biased decision-making systems.

Your Role

As a PhD candidate, you will develop innovative techniques and tools to analyze and mitigate bias propagation in automated systems. Your research will focus on the closed-loop interaction between decision-making algorithms and user behavior across diverse applications, including:

• Energy distribution
• Recommendation systems
• E-commerce
• Online advertising

By applying concepts from optimization, optimal control theory, non-linear control, and networked systems, you will investigate how bias evolves over time and explore strategies to balance fairness and efficiency in complex real-world settings.

Tasks

• Development of strategies to mitigate bias propagation and promote fairness across different applications, preferred by the candidate, such as energy distributions, recommender systems, e-commerce, online advertising
• Study of the literature on algorithmic fairness in automated decision making systems;
• Analysis of what are the key factors responsible for bias propagation in the ML algorithms;
• Analysis of the computational efficiency and efficiency-fairness trade-off of the proposed strategies;
• Empirical validation of the designed algorithms on real datasets;
• Dissemination of the results of your research in international and peer-reviewed journals and conferences;
• Writing a successful dissertation based on the developed research and defending it;
• Assume educational tasks like the supervision of Master students and internships

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

• You are an enthusiastic, open-minded young researcher who wants to have an impact in research;
• You have experience with or a background in systems and control, mathematics, physics, machine learning, data-driven modelling, signal processing;
• Preferably you finished a master's in Systems and Control,  Mechanical or Electrical Engineering, (Applied) Physics or (Applied) Mathematics;
• You work well in a team with mixed expertise, with an interest towards socio-technical applications;
• You have good programming skills and experience;
• You have good communicative skills and a cooperative attitude in the work of a research team;
• You are intellectually honest;
• You are creative and ambitious, hard-working, and persistent;
• You have good command of the English language (knowledge of Dutch is not required).

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 evaluation (go/no-go) after nine months.
• Teaching experience - to develop your teaching skills, you will spend 10% of your employment on teaching tasks.
• Interdisciplinary Research - Work at the intersection of machine learning, control theory, and ethical AI in a dynamic and ambitious university.
• Graduate Courses & Training - Access specialized coursework at the Dutch Institute of Systems and Control.
• Collaboration Opportunities - Engage with industry partners in the Brainport region and collaborate with leading researchers worldwide.
• Vibrant Research Environment - Join a dynamic Control Systems group within the Electrical Engineering department, surrounded by PhD students, postdocs, and faculty members  (around 40 research members) working on diverse real-world control applications.
• 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. €2,901 max. €3,707).
• 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.