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 one of the most consequential open questions in this space: how customer-facing AI should be designed when it speaks to real customers on behalf of a real firm. Generative voice agents now handle substantive service conversations, hand customers over to human employees, and generate content that reaches large professional audiences — yet the design decisions behind them are made largely by intuition.
We are looking for a doctoral candidate to help change that.
The position is built around three projects, all of them conducted with industry partners and all of them designed to move from controlled experiments into live operations. You will study how tightly a firm should prescribe what its AI agent says, what happens emotionally and informationally when a conversation is handed from an AI to a human colleague, and how multimodal models can predict the performance of marketing content before it is published.
Research at the Center builds on the group's track record in data science, conversational AI, and marketing analytics and on substantial investments in on-premises GPU infrastructure that allows us to work with confidential partner data under full data control. The focus of the position is on research, aiming at publications in leading international management journals.
The starting date is flexible.
Applications will be accepted until the position is filled.
Firms deploying generative voice agents must decide how tightly to prescribe what the agent says. Tight specification buys reliability, completeness and policy compliance; open specification buys adaptivity to cases nobody anticipated.
This project treats that decision as the machine analogue of the classic scripting-versus-empowerment trade-off in service operations — with the crucial difference that script strictness, an aspiration with human employees, becomes an enforceable parameter with a large language model.
The programme comprises laboratory experiments with live voice interaction, a comparison of adaptive prompting policies, and a field experiment in the live call operations of a partner in the insurance sector. Outcomes are deliberately behavioural: verified task success, conversational repair derived from transcripts, and compliance failures such as unauthorised commitments.
When a customer in a negative emotional state is transferred from a voice agent to a human employee, does the emotional acknowledgement offered by the AI carry over — or does it retrospectively read as a script if the human does not build on it?
This project examines whether the two agents jointly establish common ground about the customer's situation, and how that perceived continuity shapes whether customers feel heard and go on to recommend the provider. It progresses from a factorial experiment through studies with trained actors simulating the handover to a field implementation with the same insurance partner.
Building on an ongoing doctoral project and an established data collaboration in industrial technology, this project develops and benchmarks multimodal embedding approaches, text and image, encoded separately or jointly, as inputs to models that predict the engagement a social media post will generate before it is published.
The successful candidate will work closely with the doctoral researcher already active in this research stream.
Together, the projects give the successful candidate something rare: theoretically grounded experimental questions, partners willing to randomise in live operations, and infrastructure that makes working with sensitive conversational data possible.
Given the methodological breadth of the projects, we do not expect applicants to already be experts in every method used across the three research streams. We are looking for candidates with strong empirical foundations, intellectual flexibility, and the ability to develop additional methodological skills during the doctoral. Applications from members of underrepresented groups in academia are specifically encouraged.
The Center for AI Value at ETH Zurich, part of the Technology Marketing Group, offers an unusual combination for a doctoral researcher: theoretically ambitious questions, established collaborations with industry partners who are prepared to open their live operations to randomised studies, and the infrastructure to do the work properly.
Our research is deeply rooted in ETH's commitment to acting responsibly and innovating for societal benefit, and our team is dedicated to publishing in esteemed journals while fostering a culture of inclusivity and well-being.
The doctoral researcher will receive close scientific guidance from PD Dr. Sebastian Tillmanns and Dr. Joseph Ollier and will be embedded in the broader Technology Marketing Group led by Prof. Florian von Wangenheim.
We offer competitive one-year contracts, extendable to six years, complemented by generous travel and research allowances. New team members can count on the support and experience of colleagues working across AI in customer service, multimodal data modeling, and process automation, as well as on established experimental infrastructure for voicebot and chatbot research.
Our substantial investment in on-premises GPU infrastructure gives our researchers state-of-the-art resources for LLM training and inference — and, equally important, keeps confidential partner data within our own secure facility, which is what makes research on real customer conversations possible in the first place.
There will also be opportunities to become involved in grant applications building on the results of the doctoral research.
We look forward to receiving your online application with the following documents:
Further information about the Chair of Technology Marketing can be found on our website.
Questions regarding the position should be directed to Sebastian Tillmanns, stillmanns@ethz.ch (no applications).
Please note that we exclusively accept applications submitted through our online application portal. Applications via email or postal services will not be considered.
We would like to point out that the pre-selection is carried out by the responsible recruiters and not by artificial intelligence.
ETH Zurich is one of the world’s leading universities specialising in science and technology. We are renowned for our excellent education, cutting-edge fundamental research and direct transfer of new knowledge into society. Over 30,000 people from more than 120 countries find our university to be a place that promotes independent thinking and an environment that inspires excellence. Located in the heart of Europe, yet forging connections all over the world, we work together to develop solutions for the global challenges of today and tomorrow.
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