The Bruno Kessler Foundation (FBK) is a leading research institution based in Trento, Italy. With over 450 researchers distributed across 12 Research Centers, FBK promotes excellence in science and technology across both technical and social domains.
The internship is offered within the Intelligent Digital Agents (IDA) Research Unit of the Digital Health & Wellbeing Center. The unit focuses on developing flexible, ethically grounded technologies and digital assistants, with particular attention to Large Language Models, multi-agent systems, reasoning, human- centered AI, and digital health applications.
More information can be found at
https://ida.fbk.eu/
Planned activities
The Research Unit is looking for a Master’s student interested in pursuing an internship experience on
Agent Aggregation Strategies in Multi-Agent Large Language Model Systems.
Multi-agent systems based on Large Language Models often rely on multiple agents that analyze the same problem from different perspectives. However, the final quality of the system does not depend only on the quality of the individual agents, but also on how their outputs are combined, compared, weighted, revised, or selected.
For this reason, aggregation is a crucial bottleneck in multi-agent reasoning architectures. A weak aggregation strategy can discard correct expert outputs, amplify systematic errors, or introduce unnecessary variability, even when some agents have produced useful reasoning. Conversely, a robust aggregation mechanism can improve accuracy, support error correction, and make the overall decision process more interpretable.
The internship will focus on the Pool of Experts (PoE) framework, a multi-agent architecture in which several expert agents contribute to a shared reasoning process. The main goal is to investigate how different aggregation methods influence final system performance and whether more sophisticated aggregation strategies can improve accuracy, robustness, explainability, and consistency across tasks.
The work will compare simple aggregation methods, such as majority voting, with more advanced approaches based on deliberation, confidence estimation, role-aware weighting, disagreement analysis, meta-reasoning, and final decision-making agents. Particular attention will be given to understanding when aggregation improves the system, when it introduces new errors, and how it can be made more reliable.
Main activities include:
- Conducting a literature review on aggregation methods in multi-agent systems and Large Language Model reasoning;
- Analyzing how individual expert agents contribute to the final decision;
- Comparing aggregation methods such as majority voting, weighted voting, ranking-based selection, confidence-based aggregation, and deliberative final decision-making;
- Investigating disagreement among agents as a signal for uncertainty, ambiguity, or task difficulty;
- Designing and implementing new aggregation strategies within the PoE system;
- Evaluating whether aggregation methods recover individual agent errors or introduce new mistakes;
- Measuring the impact of aggregation on accuracy, robustness, interpretability, and consistency across tasks.
This internship offers experience at the frontier of Large Language Models, multi-agent reasoning, decision aggregation, and trustworthy AI evaluation.
Requirements
- Enrollment in a Master’s degree in one of the following fields: Computer Science, Data Science, Artificial Intelligence, Cognitive Sciences, or related disciplines;
- Fluent knowledge of English, minimum level B2;
- Strong interpersonal and teamwork skills;
- Good adaptability, initiative, and autonomy;
- Proficiency in Python;
- Familiarity with Large Language Models, generative AI, and model evaluation;
- Interest in multi-agent systems, reasoning, decision-making, or evaluation methodologies.
Additional knowledge of open-weight LLMs, prompt engineering, and statistical evaluation will be considered a plus.
Internship information
- Internship start date: second semester 2026;
- Internship experience duration: 6 months;
- Opportunity reserved for Master’s students;
- The internship experience will take place at FBK;
- We offer support in finding accommodation at affiliated facilities, in the case of off-site candidates;
- We offer the possibility to use the internal canteen service;
- Possible recognition of participation allowance.
How to Apply
Interested candidates are asked to send their application by email to:
Patrizio Bellan - pbellan@fbk.eu
The application must include the following documents in .pdf format:
- curriculum vitae;
- motivation letter.
The motivation letter is required to apply.
For any further information, please contact the Human Resources Department at: jobs@fbk.eu
Application deadline: the notice will be withdrawn when the desired applications are reached.