Sort by
Refine Your Search
-
Category
-
Country
-
Employer
-
Field
-
weather events and improve household resilience. Key responsibilities include: Data cleaning, management, and econometric analysis Supporting fieldwork design and survey development Preparing research
-
. Strong quantitative skills, with experience in econometrics and statistical analysis. Experience working with large datasets and appropriate software (e.g., Stata, R, Python, Julia, MATLAB). Excellent
-
if the necessary clean energy and energy infrastructure is available at competitive costs. Large-scale investments in the energy sector meanwhile get off the ground only if industry is prepared to electrify its
-
of the research findings. Person Specification Candidates will be expected to have a first degree in Economics or proximate fields; strong analytical skills; experience in quantitative data analysis using large
-
may include (but are not limited to): peer effects, work team design, rank effects, and managerial effects. The PhD project will be primarily empirical, with a focus on applying modern micro-econometric
-
characteristics of the case study areas. Geographical Information Systems (GIS) will be used to integrate and analyse these datasets, and a range of econometric and statistical modelling methods will be used
-
stimulating research environment composed of an ambitious and excellent faculty and a large network of research institutions and facilities. The MGSE does not charge tuition fees for attending the doctoral
-
disclosure on this topic. For instance, as of 2024, the European Corporate Social Responsibility Directive (CSRD) mandates disclosure and assurance of non-financial information for large firms. This project
-
Social Responsibility Directive (CSRD) mandates disclosure and assurance of non-financial information for large firms. This project aims to examine how various stakeholders affect the CSR challenges firms
-
quantitative discipline such as (Quantitative) Marketing, Econometrics, (Quantitative) Psychology, Data Science or related fields. Is skilled in working with time series, panel and/or unstructured data. Has