PdD candidate in computational diplomacy
Description du poste
The Science in Diplomacy Lab (SiDLab), a joint initiative between ETH Zurich and the University of Geneva established in October 2021, is recruiting a PdD candidate to serve as a research and teaching assistant at the Global Studies Institute, University of Geneva.
The successful candidate will undertake an interdisciplinary PhD at the Global Studies Institute under the supervision of Prof. Didier Wernli (Global Studies). The position is offered at an 80% activity rate, with an entry date of 1 February 2027 (or to be agreed).
The successuf candidate will work on the global governance of antimicrobial resistance from a One Health and Planetary Health perspective, using computational and data science approaches. The PhD will examine the global governance of antimicrobial resistance and infectious diseases from a One Health perspective, including its effectiveness across the human health, animal health, food systems, and environmental sectors, and will draw on multilayer network and other data science and computational approaches (e.g., Natural Language Processing) to analyse how interactions between knowledge, norms and policies shape governance outcomes. Alongside research, the teaching assistant will contribute to teaching in systems thinking, interdisciplinary, and computational diplomacy at both the bachelor and master levels.
The candidate will join an international network of collaborators across Europe, the Americas, and Asia, working alongside colleagues from computer science, social sciences, and naturel sciences.
Titre et compétences exigés
Applicants must be fluent in English and hold a master's degree in global health or a related field (global studies, international relations, global policy, environmental studies and medicine), or in computer science/computational social science.
The role requires interdisciplinary teamwork, a strong interest in the global governance of infectious diseases and on the topic antimicrobial resistance (alongside One Health, Planetary Health, and systems-thinking approaches), and competencies in data science methods including programming in Python (or R), computational text analysis, and network analysis.
Peer-reviewed publications are an asset.