Research Assistant/Research Associate (Fixed Term) Full-time

Post-Doctoral Researcher

Applications are invited for a full time post-doctoral researcher to work on an international collaboration to develop AI-based solutions for research on archival materials as part of the Humanities and AI Virtual Institute (HAVI), funded by the Schmidt Sciences Foundation.

This position is being hired for a project working on novel solutions at the interface of AI, knowledge graphs, computer vision, and the digital humanities. The goal is to develop an innovative AI architecture that is flexible and extensible enough to serve as a knowledge representation framework for the humanities. The current working prototype for this unique design avoids the pitfalls of traditional knowledge graph architecture, is transparent and interpretable, allows queries of high complexity, and has the ability to perform reasoning and generate novel insights from the represented data.

The researcher will work with Dr Sebastian Ahnert, head of the Structural Complexity research group in the Department of Chemical Engineering and Biotechnology, and an affiliate of Cambridge Digital Humanities. They will also collaborate closely with teams of faculty and researchers at the Center for Spatial and Textual Analysis, Stanford University, and at the DensityDesign Lab at the Politecnico di Milano.

We seek highly motivated and creative candidates, proficient in Python, and with expertise in one or more of the following areas: digital humanities, knowledge graphs, ontologies, graph databases, network analysis, natural language processing, computer vision. They should also have a PhD in one of the following areas: Digital Humanities, Computer Science, Physical Science, Engineering, Mathematics, Statistics, Data Science, or a closely related discipline.

Key Responsibilities

Driving the development and implementation of these key components of the project:

• A new knowledge graph architecture in the form of Python libraries, building on existing prototypes.
• A computer vision pipeline to aid knowledge graph construction.
• A prototype interface, developed in collaboration with the design team, for the interactive exploration of manuscript images and metadata.
• Effective liaison with humanities researchers to translate humanities research questions into algorithmic queries of the knowledge graph.
• Iterative development of the overall AI architecture that is responsive to the requirements of the diverse range of humanities case studies led by faculty at Stanford University as part of the team.

Fixed-term: The funds for this post are available for 2 years in the first instance.

Applications closing date 29th of March 2026.

Please quote reference NQ49054 on your application and in any correspondence about this vacancy.

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