Doctoral Researcher in Entrepreneurship
Conduct quantitative empirical research in entrepreneurship, innovation, and digital technology at the University of Luxembourg.
Best for:Best for quantitative researchers with a Master's in economics, finance, or management and strong econometric programming skills.
Overview
The University of Luxembourg invites applications for a fully funded doctoral researcher position within the Entrepreneurship, Innovation, and New Technology (EINT) research group. Working under the supervision of Prof. Christian Fisch, the candidate will pursue a cumulative, paper-based PhD thesis focusing on areas such as entrepreneurial finance, sustainable entrepreneurship, or artificial intelligence in business. The role requires strong quantitative and econometric capabilities to analyze large-scale datasets using statistical programming tools. The successful candidate will enjoy a dynamic, multilingual academic environment on the Kirchberg Campus while completing the training program of the Doctoral School in Economics, Finance and Management.
What you'll do
- Formulate original and theoretically grounded research questions in entrepreneurship and innovation
- Identify, acquire, and construct appropriate empirical datasets for quantitative analysis
- Execute rigorous statistical and econometric analyses using reproducible research workflows
- Develop research projects from initial concept through manuscript preparation, revision, and journal submission
- Disseminate findings at major international academic conferences and build professional networks
- Complete the mandatory curriculum of the Doctoral School in Economics, Finance and Management
Requirements
Degree required: Master's degree or equivalent in management, business administration, economics, finance, or a related field
Degree offered: PhD
Language: English; C1 level required
Instruction: English
- Advanced academic training in empirical research methods, statistics, or econometrics
- Practical experience in conducting quantitative empirical analysis using statistical software such as Stata, R, or Python
- Demonstrated capability in working with large-scale datasets
- Strong motivation and aptitude for independent academic research
- Applicants must demonstrate at least B2-level proficiency in the language of their thesis according to university guidelines
Funding & terms
How to apply
Prepare all required application documents including your CV, motivation letter, academic transcripts, and a writing sample. Submit your application formally through the online university recruitment portal. Applications sent via email will not be considered.
- Curriculum Vitae
- Cover letter
- Transcript of all modules and results from university-level courses taken
- Master's thesis or draft of independent written work
Contact
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