Research and Teaching Associate
- Vienna University of Economics and Business
- Research, development, teaching
- Part time
- published till: 28.10.2026
Institut für Interactive Marketing and Social Media
Part-time, 30 hours/week
Starting as soon as possible, and ending after 6 years
Do you want to find out how advertising, platforms, creators, and public policy shape what consumers buy? The position combines causal inference with large-scale real-world data and AI-based measurement, alongside teaching and work on ongoing research projects.
The Institute for Interactive Marketing & Social Media (IMSM) aims to be a leading institution for research and education in digital marketing. Our goal is to produce credible evidence that helps firms, platforms, and policymakers make better decisions and achieve better outcomes for businesses and consumers. We particularly focus on markets where digital advertising, online platforms, creator content, and AI are reshaping how consumers form brand perceptions and make purchases, and where regulators increasingly intervene. Our approach applies causal inference and machine learning, including large language models (LLMs), to large-scale observational and experimental data.
What to expect
- Writing a dissertation: You will develop and pursue your own research agenda at the intersection of digital marketing, platform economics, and empirical marketing research. Your research will be empirical and quantitative, with a strong emphasis on credible causal identification. Current research areas include:
- Platforms, regulation, and policy: How trade policy, digital advertising taxes, and platform rules affect sellers, advertisers, and consumers in online markets.
- Creator content and e-commerce: How social media content, such as TikTok videos comparing original products with lower-priced "dupes," affects brand sales and consumer choice.
- Digital advertising effectiveness and delivery: How targeting choices and platform delivery algorithms shape who sees ads and what ads achieve, studied with large-scale geo-experiments and field experiments.
- Brands, reputation, and media coverage: How scandals and publicity shape brand perceptions, separating what firms did from how loudly it was covered.
- Causal inference and AI-based measurement: Combining different econometric approaches (e.g. difference-in-differences, event-study etc.) and experimental designs with machine learning and large language models (e.g., to measure marketing constructs from text, images, and video).
- Data & infrastructure: You will work with large, proprietary, real-world datasets (e.g., from online platforms, marketplaces, advertisers, and brand-tracking providers) and modern tools for large-scale data processing.
- Responsible use of AI: You will use AI tools in coding, data processing, and measurement, and help develop good practice for validating and documenting AI-assisted work in our research and teaching.
- Conferences & network: You will present your work at leading international conferences and collaborate within our international academic network.
- Teaching & co-supervision: The regular teaching load is approx. one course per term; you will also co-supervise bachelor's and master's theses.
- Organizational tasks: As part of the team, you will support selected organizational tasks of the institute.
What you have to offer
- You hold a diploma or master's degree with strong academic performance in business, economics, marketing, computer science, data science, statistics, or a related quantitative field that qualifies you for enrollment in a PhD program at WU.
- You have a strong quantitative mindset and genuine enthusiasm for empirical research – you enjoy working with large-scale, real-world data and turning it into credible causal evidence.
- You are proficient in at least one statistical programming language (e.g., Python or R) and eager to deepen your technical skills as part of your PhD training.
- You are interested in the methods we use across the full research pipeline – automated data collection (e.g., web scraping, APIs), large-scale data processing (e.g., SQL databases), machine learning and large language models (e.g., embeddings, LLM-based annotation of text, images, or video), and causal inference (e.g., difference-in-differences, event studies, geo- and field experiments, double/debiased ML).
- You bring AI literacy and a critical, reflective approach to AI tools – you use generative AI productively, understand its limitations, and verify, validate, and transparently document AI-assisted work.
- You bring experience in or curiosity about our substantive research domains, such as digital advertising and targeting, platform algorithms, creator content and e-commerce, brand reputation, or the economics and regulation of online markets.
- You have an excellent command of written and spoken English; German language skills are an asset.
- Since the position includes teaching responsibilities, prior teaching or instructional-support experience (e.g., tutoring, grading, course assistance) is appreciated.
- You are prepared to use multimedia and digital teaching and learning formats and to help students use AI tools critically and responsibly.
What we offer you
- Six weeks of vacation/Extra vacation time
- Flexible working hours
- Training opportunities
- A wide range of benefits, from an in-house medical officer to athletic activities and a meal allowance to a variety of employee discounts
- Meaningful work in an open-minded, inclusive, and family-friendly environment
- A modern campus with spectacular architecture in the heart of Vienna
- Inspiring campus life with over 2,400 employees in research, teaching, and administration and approximately 21,500 students
- Excellent accessibility by public transportation
The minimum monthly gross salary amounts to €2,832.08 (14 times per year). This salary may be adjusted based on job-related prior work experience. In addition, we offer a wide range of attractive social benefits.
Do you want to join the WU team?
Then please submit your application by October 28, 2026 (ID 2921).
We are looking forward to hearing from you!
WU is committed to diversity and inclusion and actively encourages applications from people of all backgrounds. We particularly welcome applications from women. Not sure if your profile fully matches our requirements? Apply anyway! In case of equal qualification, female candidates will be given preference. Applicants with disabilities will be supported throughout each stage of the recruitment process. Candidates' qualifications will be assessed in the context of their academic age.
