Posting Expiry
Key dates
Application opens on February 13, 2025, 12pm ET
Optional virtual office hours on March 14, 2025, 1pm ET
Application closes on April 10, 2025, 5pm ET
What we are looking for
This is a postdoctoral fellowship program for grants of up to $250,000 USD to support early career researchers in the social sciences and humanities (with particular emphasis on philosophy, sociology of science, and metascience) who are interested in building a career in understanding the implications of AI for the science and research ecosystem.
AI (currently understood as a set of technologies including machine learning, deep learning, and foundation models) could accelerate scientific discovery, whether through narrow applications like DeepMind’s AlphaFold, or general applications such as advances in AI-enabled lab robotics, evidence synthesis, or statistical inference. There are many practical and technical challenges to solve before society has fully-fledged autonomous ‘AI scientists’. Nevertheless, it seems inevitable that over the coming years public and private R&D funders will make significant investments both to diffuse and adopt AI technologies, and to solve technical challenges, in the direction of a more heavily AI-mediated research.
This program will support a cohort of postdoctoral researchers to deepen their understanding of AI technology and pursue career paths which evaluate the phenomenon of AI-mediated science and guide its pursuit, covering one or more of the following objectives:
a) building our understanding of how the growing adoption of AI is changing the research landscape and the day-to-day work of researchers;
b) building our understanding of the epistemic, metascientific, ethical and/or socioeconomic implications of these changes; and
c) building understanding of how governments, industry, and/or funding organizations should respond to improve our research landscape.
The following are some indicative examples of topic areas of interest:
- The impact of AI on the topics and methods of scientific research, and how this varies across disciplines
- AI and the pace of scientific progress
- Explainability and alignment in scientific AI
- The skills and training implications of scientific AI
- The role of humans in AI-driven science
- Epistemic and ethical considerations concerning the application of AI in the production of research outputs and the assessment of research