At the Center for AI Value, part of the Technology Marketing Group at ETH Zurich, we investigate how organisations can turn generative and multimodal AI into measurable value. Our current focus is on how customer-facing AI should be designed when it interacts with real customers on behalf of a firm. The position is built around three projects, all conducted with industry partners and designed to move from controlled experiments into live operations. The focus is on research, aiming at publications in leading international management journals.
Tasks
- Design and run controlled experiments, including studies with live voice interaction, and prepare them for pre-registration.
- Use and extend the Center's existing experimental infrastructure for these studies, including prompt design as a controlled manipulation, generative voice agent pipelines, conversation logging and transcription.
- Extend and validate existing LLM-based coding pipelines for transcript-derived measures, including validation against human-coded gold standards.
- Analyse experimental and operational data using appropriate causal and psychometric methods.
- Prepare and coordinate field experiments within established industry collaborations and in close coordination with senior researchers, including feasibility assessment, randomization design, and retrieval of operational outcomes.
- Work with multimodal embedding models and machine learning methods for content performance prediction.
- Present results at international conferences and to partner organisations.
- Contribute to teaching and supervise Master's theses within the Center's focus areas, alongside a limited share of administrative duties.
Requirements
- Possess a Master of Science (MSc), Master of Arts (MA), or Master of Philosophy (MPhil) degree in business administration, computer science, or related fields, including psychology, mathematics, engineering, physics, or statistics.
- Candidates from technical backgrounds are welcome but should be motivated by managerial and behavioural research questions rather than model development as such.
- A demonstrated interest in management-related disciplines is highly desirable.
- Currently residing in Europe.
- Strong interest in experimental research and quantitative empirical methods.
- Exhibit excellent organizational skills, including the ability to manage and prioritize multiple tasks effectively.
- Strong communication and writing skills in English for effective collaboration and preparation of scientific publications and reports.
- Fluency in both spoken and written English is mandatory.
- Take initiative, be results-oriented, organized, and demonstrate creativity in problem-solving.
- Strong empirical foundations, intellectual flexibility, and the ability to develop additional methodological skills during the doctoral period.
- Applications from members of underrepresented groups in academia are specifically encouraged.
Benefits
- Theoretically ambitious research questions and established collaborations with industry partners prepared to open live operations to randomised studies.
- Access to substantial on-premises GPU infrastructure for LLM training and inference, ensuring confidential partner data remains secure.
- Competitive one-year contracts, extendable to six years, with generous travel and research allowances.
- Close scientific guidance from senior researchers and integration into the Technology Marketing Group.
- Support and experience from colleagues working across AI in customer service, multimodal data modeling, and process automation.
- Opportunities to become involved in grant applications building on the results of the doctoral research.
- Inclusive culture, equality of opportunity, and a working environment that values diversity and sustainability.
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Das Team
The doctoral researcher will receive close scientific guidance from senior researchers and will be embedded in the broader Technology Marketing Group, working alongside colleagues with expertise in AI in customer service, multimodal data modeling, and process automation.