DescriptionThe Senior Research Associate will play a central role in designing and running AI-driven experiments, developing and applying large language models and generative AI methods, building and maintaining large-scale research datasets, and contributing to original research on how artificial intelligence shapes - and is shaped by - knowledge production and diffusion. The Senior Research Associate will be expected to take an active role in obtaining and carrying out funded research (they can serve as PI on reseach projects) and may supervise student researchers. There are no teaching responsibilities.
The University of Chicago Knowledge Lab (PI Professor James A. Evans) is at the forefront of research at the intersection of artificial intelligence and collective knowledge - building AI systems that think differently from humans and, in doing so, expand what humanity can discover. Current projects include developing time-aware large language models to predict scientific breakthroughs and direct research funding toward high-impact opportunities, designing AI agents that augment human reasoning across science, policy, and society, and constructing "virtual laboratories" that simulate potential futures in science and technology. This work is published in Nature, Science, and PNAS, and has been supported by the NSF, NIH, DARPA, the John F Templeton Foundation, the Novo Nordisk Foundation, among others.
Applicants with experience with machine learning, LLMs, and computational social science methods, as well as a demonstrated interest in empirical research on AI, collective intelligence, or scientific discovery are preferred. The successful candidate will work under the supervision of Professor James A. Evans and in collaboration with faculty across the University of Chicago and partner institutions.
QualificationsPrior to the start of employment, qualified applicants must possess:
- a Ph.D. in the social sciences (e.g., sociology, economics, political science, communications) or computational sciences (e.g., computer science, informatics/information science, engineering, data science, applied mathematics, statistics, physics), or a related field.
- Proficiency in Python and experience with large language models and generative AI frameworks (e.g., Hugging Face Transformers, PyTorch) is required.
We especially welcome applicants with:
- Active publication record and engagement with the broader scientific community, ideally in venues at the intersection of AI, computational social science, or science of science.
- Strong writing skills and experience contributing to research manuscripts, grant proposals, or technical reports.
- Experience designing and running computational experiments, including hypothesis formation, testing, and iteration at scale.
- Expertise in large language models, generative modeling, or related deep learning methods; familiarity with fine-tuning, prompt engineering, or model evaluation pipelines is a strong plus.
- Experience working with large-scale text corpora, bibliometric data, or other unstructured data sources relevant to knowledge and information systems.
- Familiarity with social and semantic network analysis, embedding models, or other methods for representing and analyzing knowledge structures.
- Comfort working in Linux/Unix environments and on high-performance computing clusters.
- Ability to work effectively in a highly collaborative, interdisciplinary environment spanning sociology, computer science, and data science.
- Strong communication skills, including the ability to translate complex technical methods for diverse audiences.
- Demonstrated ability to work independently, prioritize across multiple projects, and bring creative, resourceful approaches to research problems.
Application Instructions To be considered, those interested must apply through The University of Chicago, Academic Recruitment job board, which uses Interfolio to accept applications: https://apply.interfolio.com/192473
Applicants must upload:
- CV/Resume
- Cover Letter (1-2 pages)
- Research Statement
- List of Potential References with name and contact information (3-5)
The review of applications will begin after the position has been posted for 30 days and will continue until the position is filled.
For instructions on the Interfolio application process, please visit http://tiny.cc/InterfolioHelp.
