PhD Candidate: Macro Forecasting & Data Science

Master in Integrated Building Systems ETH Zürich; Zürich; Vor Ort; CHF 60.000 - 80.000; Vollzeit

Benefits dieser Stelle

Health benefits

Flexible working hours

Professional development

Childcare

Zusammenfassung

KOF Swiss Economic Institute at ETH Zurich invites a PhD student to join its Macroeconomic Forecasting and Data Science team. The role focuses on publishing quarterly outlooks, developing forecasting models, and handling macroeconomic and high-frequency datasets.

The candidate will pursue a high-quality dissertation in applied macroeconomics and macroeconometrics, leveraging machine learning and data pipelines within ETH Zurich's renowned environment.

Qualifikationen

• Strong knowledge of time series econometrics and forecasting methods.
• Experience with large datasets, nowcasting, and forecasting evaluation.
• Excellent quantitative and programming skills and ability to communicate results clearly.

Aufgaben

• Participate in the preparation of the international economic outlook as part of the quarterly publication of KOF economic forecasts.
• Pursue an excellent PhD dissertation in applied macroeconomics, macroeconometrics, or economic nowcasting and forecasting.
• Develop, implement, and evaluate new forecasting and nowcasting models using econometric and machine learning methods.
• Analyse large-scale macroeconomic and high-frequency datasets to improve economic forecasting.
• Develop and maintain reproducible code, data pipelines, and research software.

Kenntnisse

Time-series econometrics

Forecasting methods

Data analysis

Machine learning

Languages (German/English)

Programming

Ausbildung

Master’s degree in Economics/ econometrics/ data science

Jobbeschreibung

KOF Swiss Economic Institute at ETH Zurich invites a PhD student to join its Macroeconomic Forecasting and Data Science team. The role focuses on publishing quarterly outlooks, developing forecasting models, and handling macroeconomic and high-frequency datasets.

The candidate will pursue a high-quality dissertation in applied macroeconomics and macroeconometrics, leveraging machine learning and data pipelines within ETH Zurich's renowned environment.