Doctoral Student in Operational Decision Making with Data Science
Doctoral Student in Operational Decision Making with Data Science at ETH Zürich
The Decision Sciences and Analytics group at ETH Zürich is recruiting a doctoral student to work on operational decision making with data science. The project is led by
Prof. Tu Ni
and sits at the intersection of operations management, data science, experimental design, and causal inference. The research aims to develop experimental and causal methods for efficient and robust evaluation of new products, policies, and technologies in modern organizational settings, with connections to industrial partners in online marketplaces.
This PhD opportunity is well suited to candidates interested in data-driven decision making, policy-relevant research, and real-world business applications. The successful student will help develop methods for experimental and causal evaluation, work with industry partners on implementation, and contribute to high-quality papers targeting top-tier operations management journals. There is also scope to define and pursue individual research questions within the broader theme of data-driven decision making.
Alongside research, the role includes light duties such as teaching and lab activities. ETH Zürich highlights a collaborative and dynamic research environment, along with a strong commitment to diversity, equality of opportunity, and sustainability.
Eligibility highlights:
applicants should have excellent academic results and a completed or near-completed Master’s degree in statistics, operations, economics, or a closely related field. Strong skills in statistics, optimization, stochastic modeling, and communication are expected; experience with real A/B testing is advantageous.
Funding and appointment:
the position is initially offered for 18 months, with the prospect of extension for a four- to five-year doctoral duration subject to satisfactory progress. Gross salary will follow ETH Zurich regulations.
How to apply:
submit an online application through ETH Zurich’s portal. Include a motivation letter, CV, complete academic transcript/record, and contacts for at least two references. Applications by email or post are not accepted. For questions about the position, contact Tu Ni at [email protected].
Institution:
ETH Zürich, Switzerland.
