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Aurelie Lemmens

1 week ago

PhD Position: Algorithmic Bias and Fair Machine Learning in Marketing Erasmus University Rotterdam in Netherlands

I am recruiting a PhD student to work on algorithmic bias and fair machine learning in marketing at Erasmus University Rotterdam.

Erasmus University Rotterdam

Netherlands

email-of-the@publisher.com

Jan 15, 2026

Keywords

Computer Science
Deep Learning
Marketing
Public Policy
Consumer Behavior
Business
Open Science
Reinforcement Learning
Causal Inference
Active Learning
Bias
Discrimination Studies
Econometric
Economics
Field Experimentation
Marketing Analytics
Statistic
Machine learning

Description

The Rotterdam School of Management (RSM) at Erasmus University Rotterdam is offering a fully-funded PhD position focused on the critical issue of algorithmic bias and fairness in marketing. As artificial intelligence and machine learning increasingly guide marketing decisions, the risk of reproducing or amplifying human biases through algorithms has become a significant managerial and societal challenge. This project aims to understand and address algorithmic biases in targeted marketing campaigns, developing new methodological frameworks for designing effective and fair personalized policies. The research will involve large-scale field experiments in collaboration with industry partners, leveraging causal machine learning, active learning, and policy evaluation techniques. The PhD will be supervised by Professor Dr. Aurelie Lemmens and is funded by a prestigious VICI NWO grant. The marketing group at RSM is internationally recognized, publishing in top journals and fostering a collaborative, diverse, and open science-oriented environment. PhD students benefit from expertise in reinforcement learning, deep learning, causal inference, field experiments, consumer behavior, and behavioral economics. The program includes coursework in machine learning, economics, statistics, econometrics, and quantitative marketing, tailored in consultation with advisors. Candidates will work closely with faculty to identify novel research questions, develop and code algorithms, analyze experimental and observational data, and present findings at international conferences. The project is interdisciplinary, combining economics, computer science, marketing, and management, with potential behavioral research on consumer perceptions of algorithmic discrimination. Applicants should have a strong quantitative background (MSc or equivalent) in relevant fields, programming experience (R/Python), excellent English skills, and a passion for fairness and societal impact. The position offers a competitive salary (€3,059–€3,881/month), full employment benefits, and funding for a 3-6 month international research visit. The department values diversity, inclusion, and open science practices. The expected outcome includes high-impact publications and an open-access web platform for sharing data, code, and tutorials. The application deadline is January 15, 2026. For more information, candidates can consult the supervisor’s academic page and the RSM department website.

Funding

Available

How to apply

Apply via the Erasmus University Rotterdam online application portal. Prepare all required documents as specified by ERIM. Attend the virtual open house in December for more information. For questions, consult the Admissions page or contact the university by email.

Requirements

Applicants must have a quantitative education (MSc or Research MSc) in econometrics, computer science, mathematics, physics, economics, or quantitative marketing. Experience in programming (R and/or Python) is required. Candidates should have a strong interest in societal problems, especially fairness and ethics, and a passion for real-world organizational challenges. Excellent English speaking and writing skills are necessary, ideally with experience writing for a scientific audience. Intellectual curiosity, motivation for an international academic career, commitment to methodological rigor and scientific integrity, and strong organizational skills are expected. Interdisciplinary interest in both methodological and behavioral aspects is valued.

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