Vacature PHD Recruitment

Doctoral Research in Marketing, specialized in quantitative methods (marketing science, computer science, machine learning)

The marketing group at Rotterdam School of Management, Erasmus University seeks highly motivated PhD students looking to study topics in marketing. Our group is unique in the Netherlands by focusing on developing and applying state-of-the-art methodologies from the fields of statistics, economics, and machine learning. Our faculty combines our methodological expertise with a deep understanding of the challenges businesses face. As part of a business school, we have strong ties with industry (profit and nonprofit) and government that allow our research to have direct societal impact. Strong applicants typically have backgrounds in computer science, statistics or econometrics and are looking to pursue careers as world-class academic researchers. Students define and execute their own projects in consultation with their advisers and thus need creativity, self-direction, and a passion for scientific research. We are looking for candidates that are equally interested in solid academic research and in addressing real-world problems.

Our PhD program seeks to train the next generation of marketing academics. We want our students to maximize their potential and become independent marketing scholars. We expect students to become experts in a specific domain of choice. This vacancy is explicitly targeted at candidates interested in using or developing quantitative approaches to tackle real-world challenges based on advanced machine learning and other statistical methods and/or candidates with a strong interest in marketing research applications of immersive technologies. The application is not limited to a specific topic within this domain. Instead, the PhD candidate will define a research agenda around a topic of their choosing based on their own expertise, interests and fit with one or several of our faculty members. As such, PhD positions in our group are open. During their years of study, students define and execute their own projects. They do this in consultation with their advisers, but also work with other faculty, including those at other institutes. The faculty in the quantitative group in our department work on a wide range of topics, such as design of multi-armed bandits and reinforcement learning models with applications to recommendation systems and clinical trials (Gui Liberali), virtual / augmented / mixed reality (Yvonne van Everdingen), digital platform markets (David Kusterer), privacy (Gilian Ponte), behavioral economics (Alina Ferecatu), causal inference (Jason Roos), marketing strategy (Gerrit van Bruggen), consumer eye tracking (Ana Martinovici), deep learning (Sebastian Gabel), consumer and firm networks (Xi Chen), customer analytics (Aurélie Lemmens), consumer learning () and quantitative modelling approaches to predict the psychological processes involved in consumer judgments and decisions (Antonia Krefeld-Schwalb and Dan Schley).

In addition to standard required course work, students typically take courses in machine learning, (micro)economics, statistics, causal inference, econometrics, and seminars in quantitative marketing. The exact portfolio of courses is chosen in consultation with the advisers.

Approach

• Identifying novel research questions based on real-world phenomena.
• Understanding the theoretical foundations and state-of-the-art models in marketing science, economics, psychology, and computer science literatures relevant to understanding the phenomena.
• Identifying the fundamental variables, trade-offs and relationships that are most important to studying the phenomena.
• Developing and coding the appropriate algorithms and methods that implement the novel concepts and models.
• Gathering experimental or observational data to highlight the strength and boundaries of the proposed methods.
• Identifying the critical assumptions needed to draw inferences from empirical results.
• Writing computer code to analyse experimental or secondary data according the best practices and tools including versioning (e.g., GitHub), pre-registration, data sharing and open science (e.g., Figshare).
• Presenting research findings at international conferences, in our PhD day and brownbag seminars.
• Writing up findings for publication in international journals.
• Attending classes and seminars (including those offered at other universities) to further develop thinking and research skills.
• Participating in and contributing to departmental research functions (PhD Day, research seminars, weekly research meetings).
• Teaching students (to a limited degree).

Through workshops, research seminars, applied and theoretical research with faculty, and seminars on key disciplines that provide the foundations of the marketing discipline (statistics, economics, psychology), the PhD student will gain the requisite experience for independent work.

Students have access to world-class research facilities :

• High-performance computing is available to researchers via SURFSara (a Dutch consortium for scientific computing)
• State-of-the-art virtual reality (VR) lab in which we conduct VR (and AR) research, integrating VR with eye-tracking and physiological measurements.
• Erasmus Behavioral Lab
• Excellent research funding

Required Profile

We seek candidates with the following qualities:

• Intellectual curiosity, drive, eagerness to learn, and openness to criticism and other perspectives
• Strong motivation to pursue an international career as a leading scholar
• Strong commitment to methodological rigor and scientific integrity
• Strong passion for real-world problems faced by different types of organizations
• Excellent speaking and writing ability in fluent English, ideally with experience writing for a scientific audience
• Willingness and motivation to independently formulate research projects and carry them through to completion
• Excellent organizational skills
• Masters' degree (preferably a Research Master's or MPhil degree) in one of the following fields: computer science, data science, operations research, economics, econometrics, quantitative psychology, statistics, management, or marketing.
• The ideal candidate should also have some experience in programming (e.g., R, Python, Julia, Scala, Java, or C++) and in data analysis, management, preparation, and visualization, ideally as part of at least one end-to-end data science project.

One feature that sets RSM apart from other faculties is the extent of cross-discipline work between the quantitative faculty (trained primarily in machine learning, operations research and economics) and the behavioral faculty (e.g., trained primarily in psychology and neuroscience). Thus, we are also explicitly inviting applications of students who would like to work at the intersection of quantitative marketing and consumer behavior. For example, if the PhD student was working on immersive technologies, their research could benefit from in-depth training in the psychology of consumer judgment and decision-making. In that case, we encourage candidates to explicitly mention it in their application (e.g., in the motivation letter and/or research statements).

Required by ERIM

All application documents required by ERIM can be found here: https://www.erim.eur.nl/doctoral-programme/phd-in-management/admissions/application/

Interested candidates are invited to visit the ERIM PhD in Management website ( http://www.erim.eur.nl/doctoral-programme/ ) for information about application procedures and criteria. If you have any questions about the formal admission requirements, please contact the ERIM doctoral office: or Dr. Anne Kathrin Klesse ( ).

If you are interested in our PhD program and consider applying, we invite you to join us on November 23 at 6pm to 8pm CETOR on November 27 at 10am to 12pm CET . In these info sessions we provide you with lots of information on our PhD program, department, and school.

Expected output

You will generate research that can be published in top-tier peer-reviewed journals in marketing, such as Marketing Science, Management Science, Journal of Marketing Research, and Journal of Marketing. The research group at RSM has a strong record publishing in these and other top journals in related fields, including Management, Psychology, Neuroscience, and Economics. The final results of the PhD project are published in a PhD dissertation, and most marketing PhD dissertations at RSM find their way into top journals. In addition, we strongly encourage our members to publish their codes on open-science platforms and create packages to generate more impact and adhere to the principle of Open Science.

Cooperation

To strengthen your international research network and complement your time at RSM, you will receive funding for a 3- to 6-month research visit. Past and on-going visits have included Stanford, MIT, Wharton, Chicago, Columbia, Harvard, Colorado, Cornell, and UCLA. We also strongly encourage collaboration with our business partners who are active in multiple domains (digital, retail, consumer goods, nonprofits, B2B, fintech, etc.).

Societal relevance

PhD students are encouraged to pursue topics that not only improve the practice of marketing, but also consumer or societal well-being (e.g., algorithmic fairness), and thus align closely with the school's mission to be a force for positive change in the world.

Scientific relevance

PhD research should be of the highest quality, carried out with scientific rigor and the utmost integrity. The department values openness and encourages students to embrace the principles and tools of open science (e.g., making code and data available to others and pre-registering experiments). The marketing group conducts research in our core field of marketing, as well as related disciplines outside marketing. Our diversity and interdisciplinarity make the department a lively, creative, and intellectually stimulating place to conduct research.

You may also look at the work done by several expert practices at ECDA:

PhD Recruitment

Reference ERIM PhD 2024 RSM MKT RIM Deadline Monday, 15 January 2024

Functie:	phd recruitment
Startdatum:	01-11-2023
Ervaring:	Ervaren
Educatielevel:	WO
Contracttype:	Vast
Salaris:	onbekend – onbekend
Uren per week:	1 – 40

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