PhD Candidate: Macro Forecasting & Data Science

Emerging Scholars Council; Zürich; Vor Ort; CHF 70.000 - 90.000; Vollzeit

Benefits dieser Stelle

Health benefits

Flexible working hours

Professional development

Childcare

Zusammenfassung

KOF Swiss Economic Institute at ETH Zurich is seeking a PhD Student in Macroeconomic Forecasting and Data Science. The position is available immediately and should be filled as soon as possible.

The role combines macroeconometric modelling with data science for nowcasting and high-frequency indicators. You will work on the international economic outlook, pursue a high-quality PhD, and develop/review forecasting models while handling large datasets.

Qualifikationen

• Master's degree in Economics, Econometrics, Data Science, Statistics or a closely related quantitative field.
• Strong knowledge of economics and economic policy issues.
• Excellent quantitative and programming skills with time series and forecasting methods.

Aufgaben

• Participate in preparing the international economic outlook for the quarterly forecast publication.
• Pursue an excellent PhD dissertation in applied macroeconomics or nowcasting.
• Develop, implement, and evaluate forecasting and nowcasting models using econometric and ML methods.
• Analyze large-scale macroeconomic and high-frequency datasets to improve forecasting.
• Develop and maintain reproducible code and data pipelines.

Kenntnisse

Time series econometrics

Forecasting methods

Data science

Programming

English communication

German proficiency

Ausbildung

Master's degree or higher

Tools

R

Python

MATLAB

Jobbeschreibung

KOF Swiss Economic Institute at ETH Zurich is seeking a PhD Student in Macroeconomic Forecasting and Data Science. The position is available immediately and should be filled as soon as possible.

The role combines macroeconometric modelling with data science for nowcasting and high-frequency indicators. You will work on the international economic outlook, pursue a high-quality PhD, and develop/review forecasting models while handling large datasets.