Fully funded Postdoc Position with a targeted commencement date of October 1, 2023. The project on organizational learning from product failure in the pharmaceutical industry is funded by the Swiss National Science Foundation (SNSF) for three years. The applications period is ongoing until the position is successfully filled.

Project background
This project seeks to study how organizations learn from product failures, including product recalls, and the subsequent impact on the organization and its stakeholders. Focusing on the pharmaceutical industry and specifically on the safety of medications, the study seeks to analyze data sourced from clinical trials, FDA reports, social media platforms, and patient-driven communities. The objective is to detect potential hazards and evaluate their consequences The research delves into the impact of drug recalls on an organization's future product development and overall product portfolio, as well as its repercussions on various stakeholders, especially patients suffering from rare or difficult-to-treat diseases. The aspiration is to engage in academic research that can also advance knowledge for the betterment of practitioners and patients.

Job description
As a postdoctoral scholar you will conduct research at the interface between Strategic Management and Organization Theory. Employing cutting-edge quantitative methodologies, your role will involve examining the influence of product failures on diverse stakeholders. In your role as a postdoctoral researcher, a primary expectation is that your academic efforts will be devoted to this project. Moreover, you are strongly encouraged to contribute your unique research ideas, provided they align with the overarching research trajectory of the project.

Your profile

• Hold a Doctoral degree in management, economics, engineering, or in related fields such as psychology or sociology (or nearing completion of your degree) from a reputable business/engineering program and University.
• Possess a strong enthusiasm for conducting research in the pharmaceutical/medical domains, utilizing quantitative techniques, with the dual objective of publishing in leading academic journals and driving advancements beneficial for practitioners and patients dealing with difficult-to-treat or rare disease.
• Demonstrate analytical skills and solid knowledge of econometrics.
• Exhibit proficiency in spoken and written English.
• Ideally, exhibit solid programming skills in Python and an affinity with AI/NLP/ML, possess a robust background and expertise in a pharmaceutical-related discipline.

Application Instructions