ETH Zurich
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PhD in ML and Econometric Nowcasting Models at ETH Zurich ETH Zurich in Switzerland
Degree Level
PhD
Field of study
Computer Science
Funding
PhD opening at ETH Zurich / KOF Swiss Economic Institute. The post says the position starts for 18 months initially and can extend to a full 4-5 year PhD; no stipend amount or tuition details are stated.
Deadline
Sep 15, 2026
Country
Switzerland
University
ETH Zurich

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About this position
PhD opportunity at ETH Zurich (KOF Swiss Economic Institute), Zurich, Switzerland. The project focuses on building machine learning and econometric nowcasting models using large-scale, real-time macro datasets. It is a strong fit for applicants interested in time series econometrics, forecasting evaluation, and reproducible data pipelines, with an applied macroeconomics/data-science flavor.
The post explicitly announces a PhD opening. The position is located in Zurich, Switzerland and is described as 18 months initially, with the possibility of extension to a full 4–5 year PhD.
Eligibility highlights: a Master's degree in Economics, Econometrics, Data Science, or Statistics is requested. Good German is required, and French or Italian is a plus.
Funding: the post indicates a PhD appointment with an initial 18-month period and potential extension; no stipend amount, tuition waiver, or other financial details are provided in the post.
How to apply: use the ETH Zurich jobs link to open the vacancy page and submit your application through the official portal. Make sure to apply before the stated deadline of 2026-09-15.
Funding details
PhD opening at ETH Zurich / KOF Swiss Economic Institute. The post says the position starts for 18 months initially and can extend to a full 4-5 year PhD; no stipend amount or tuition details are stated.
What's required
Master's degree in Economics, Econometrics, Data Science, or Statistics. Good German is required; French or Italian is a plus.
How to apply
Apply through the ETH Zurich jobs portal using the provided job link. Review the posting details and submit the application before the deadline.
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