Internship Opportunity: Application of Large Language Models for Sentiment Analysis of User Reviews.

Fondazione Bruno Kessler (FBK) is a leading research and innovation organization based in Trento, Italy. With over 450 researchers across 12 Research Centers, FBK operates in diverse scientific and technological fields, organized into two main clusters: Technology & Innovation and Humanities & Social Sciences. More information: Within this context, the MoDiS (MOtivational DIgital Systems) Research Unit is part of the Digital Society Center and focuses on the development of methodologies and technologies that promote user engagement, motivation, and behavior change. Particular attention is given to game-based and persuasive techniques that enable the personalization of digital experiences, applied across domains such as education, sustainable mobility, and waste reduction. More information: The Digital Society Center conducts interdisciplinary research and develops digital technologies to address challenges in areas such as integrative AI, intelligence at the edge, and socio-technical systems. The center fosters collaborations with public administrations, industry partners, and academic institutions to support the digital and green transition and to build a more sustainable society.Planned Activities The MoDiS Research Unit is seeking a motivated intern with a strong interest in Artificial Intelligence and Software Engineering applied to scientific research workflows. The internship will focus on the automation of data extraction from users’ comments using Large Language Models (LLMs).Working closely with MoDiS researchers, the intern will contribute to the following activities: Analysis of the current literature in Natural Language Processing, Sentiment Analysis and Information Retrieval; Design and implementation of pipelines integrating LLMs (e.g., GPT-based tools) to discover frequent topics from user reviews retrieved from commercial platforms like Steam and Reddit, analyze sentiment, and identify the most relevant topics; Development of prompt engineering strategies and/or fine-tuning approaches; Evaluation of pipeline performance and comparison with traditional NLP workflows. The internship will offer the opportunity to work in a collaborative and multidisciplinary environment and gain hands-on experience in applied research at the intersection of AI and behavioral science.Requirements Master’s degree (or near completion) in Computer Engineering, Telecommunications, Electrical Engineering, or Computer Science; Interest in Natural Language Processing, Large Language Models and Software Engineering; Knowledge of Object-Oriented Design and/or Model-driven Engineering; Good programming skills (preferably Python); Familiarity with LLM libraries and frameworks (e.g., OpenAI API, Hugging Face Transformers); Good communication and collaboration skills; Fluency in written and spoken English (minimum B2 level; no certificate required). Internship Information Type: Curricular internship (no allowance); Duration: 3 to 6 months, depending on the candidate’s needs and preparation; Location: Remote, hybrid or in presence at Povo (Trento, Italy). Other benefits: Access to the internal canteen (except for UniTN students); Supportive, interdisciplinary research environment; Support for the search for accommodation at the affiliated structures (no allowance) Additional Opportunities: This internship may be extended into a full research thesis for interested candidates.ApplicationPlease make sure that your application contains the following attachments (in pdf format): Detailed CV including relevant past experiences (as an attached document in PDF format); Cover Letter (explaining your motivation for this specific position). For further information regarding the application, please contact Federico Bonetti at