Pre-Doctoral Researcher: Data-Driven Energy Transitions

EURAXESS Ireland; Wien; Hybride; EUR 29 000 - 35 000; Temps partiel

Avantages offerts par ce poste

Six weeks of vacation

Training opportunities

Wide range of benefits

Meaningful work

Modern campus

Inspiring campus life

Excellent public transport access

Résumé du poste

WU Vienna University of Economics and Business offers a part-time pre-doctoral researcher position (30 hours/week) at the Institute for Data, Energy and Sustainability (IDEaS). The role begins January 1, 2027 and ends September 30, 2029, focusing on data-driven analysis of energy transitions and climate action.

You will design data pipelines, harmonize diverse sources using NLP/LLMs, and apply econometric methods to generate insights for policy and industry partners.

Qualifications

• Master's degree in a quantitative/analytical field (data science, CS, IS, stats, math, physics, econ, or engineering).
• Experience constructing datasets from unstructured sources and building data pipelines.
• Training in econometrics or statistics.
• Interest in energy transition and climate topics.

Responsabilités

• Conduct research for the IDEaS projects, build datasets and data pipelines, and publish in peer-reviewed journals.
• Pursue a PhD at WU and dedicate one third of working hours to the dissertation.
• Co-supervise bachelor's and/or master's theses.
• Engage with external stakeholders in industry, government and academia to co-develop insights.
• Support organizational duties and teaching activities within the institute.

Connaissances

Building datasets

Coding

Empirical analysis

Energy & climate interest

Formation

Master's degree

Outils

Python

R

Description du poste

WU Vienna University of Economics and Business offers a part-time pre-doctoral researcher position (30 hours/week) at the Institute for Data, Energy and Sustainability (IDEaS). The role begins January 1, 2027 and ends September 30, 2029, focusing on data-driven analysis of energy transitions and climate action.

You will design data pipelines, harmonize diverse sources using NLP/LLMs, and apply econometric methods to generate insights for policy and industry partners.