Doctoral Student in Operational Decision Making with Data Science

The Decision Sciences and Analytics group, led by Prof. Tu Ni at ETH Zürich is seeking a doctoral student to study operational decision making with data science. This position focuses on the development of experimental and causal methods for efficient and robust evaluation of new product, policy, and technology in modern operational context of organizations. The research is connected to several industrial partners in online marketplaces. 

• Develop new methods for experimental and causal evaluation that are relevant in real business
• Work with industrial partners on implementing the methods
• Write high-quality papers and publish on top-tier OM journals
• They will also have the opportunity to develop their own research questions within the broader topic of the data-driven decision making
• In addition to research activities, they will contribute to light tasks and responsibilities (e.g. teaching, lab activities) 

• Excellent academic results and is motivated to produce high-quality, policy-relevant research
• Hold (or will have completed at the time of appointment) a Master’s degree in statistics, operations, economics, or a closely related field
• Have excellent analytics skills: statistics, optimization, stochastic modeling, etc
• Have excellent verbal and written communication skills
• Have experience in working on real A/B testing is a plus

• The starting date is negotiable
• The position is initially offered for 18 months, with the prospect of extension for four- to five-year duration of the doctorate, subject to satisfactory progress 
• We offer the opportunity to pursue a high-quality PhD at a renowned institution and to work in a dynamic and collaborative research environment
• Gross salary will be in accordance with the regulatons of ETH Zurich

We look forward to receiving your online application with the following documents:

• A letter of motivation that includes an explanation why you are interested in doing a PhD and fit for the position (within one page)
• A resume/CV
• Complete academic record with undergraduate and graduate courses and grades
• Contact of at least two references

Further information about Department can be found on our Website. Questions regarding the position should be directed to Tu Ni, [email protected] (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.