The Content-Centered Computing <https://www.cs.unito.it/do/gruppi.pl/Show?_id=453y> group at the University of Turin, Italy, offers *two 14-month postdoc positions* in the context of HARMONIA (Harmony in Hybrid Decision-Making: Knowledge-enhanced Perspective-taking LLMs for Inclusive Decision-Making), funded by the European Union under the NextGenerationEU program within the larger project FAIR (Future Artificial Intelligence) Spoke 2 "Integrative AI" <https://fair.fbk.eu/>. The project aims at developing methods for the adoption of knowledge-enhanced Large Language Models (LLMs) in supporting informed and inclusive political decisions within public decision-making processes.
The topics of the postdoc fellowships are: - Computational linguistics methods for knowledge-enhanced perspective-taking LLMs to support Inclusive Decision-Making - Perspective-taking LLMs for supporting Inclusive Decision-Making (full descriptions below) The team includes members of the Computer Science Department and Economics and Statistics Department of the University of Turin. A PhD in Computer Science, Computational Linguistics, or related areas is highly recommended. Knowledge of Italian is not mandatory. The deadline for application is *May 13th 2024*. The gross salary is €25.328 (about €1,860/month net salary). Turin <https://www.turismotorino.org/en/territory/torino-metropoli/torino> is a vibrant and liveable city in Northern Italy, close to the beautiful Italian Alps and with a manageable cost of living <https://en.unito.it/living-turin/when-you-arrive/cost-living-turin>. Link to the call <https://www.turismotorino.org/en/territory/torino-metropoli/torino> (in Italian). Link to the application platform <https://pica.cineca.it/unito/assegni-di-ricerca-unito-2024-i-pnrr/>. Please write to <[email protected]> or <[email protected]> for further information on how to apply. Best regards, Valerio Basile -- *Computational linguistics methods for knowledge-enhanced perspective-taking LLMs to support Inclusive Decision-Making* The activity will focus on a) design of a semantic model to represent interactions between urban services and citizens and integrate multi-source hybrid data; b) data annotation by citizens with different socio-cultural backgrounds to collect different perspectives on social issues. Data will be collected and organized in a Knowledge Graph. The activity will be supported by an interdisciplinary team of experts in KR, behavioral economics and LLMs (link with the design of knowledge-enhanced LLMs). *Perspective-taking LLMs for supporting Inclusive Decision-Making* The activity will focus on a) exploring techniques for integrating multi-source hybrid citizen data into LLMs (RAG and Knowledge Injection); b) developing methods for training and evaluating perspective-taking LLMs, which explicitly encode multiple perspectives, embodying the point of view of different citizen communities on a topic. Planned activities include: benchmark creation, error analysis, and evaluation of the efficiency and reliability of the developed technologies.
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