MULTI-MODAL KNOWLEDGE GRAPH FOR HEALTHCARE

The Bruno Kessler Foundation is a research and innovation institution based in Trento. The Foundation operates in a plurality of disciplinary fields and aims to achieve excellence in science and technology through 2 science clusters, one dedicated to technology and innovation and one to humanities and social sciences, organized in 12 Research Centers, and with more than 450 researchers. For more information visit https://www.fbk.eu/it/chi-siamo/.

In this context, the Intelligent Digital Agents Unit focuses on the study and development of flexible technologies and prototypes of digital assistants in the sector of prevention and mental well-being.
More information about IDA at https://ida.fbk.eu/home.

Planned activities

The IDA Unit of the Digital Health and Well Being Center is looking for a bachelor/master student interested in pursuing an internship in knowledge engineering, with a specific focus on multi-modal knowledge graphs (MMKG) for healthcare. The internship will be centered on work related to the Multi-Modal Knowledge Graph Supporting Personalized Health (FuS-KG), currently under development within the IDA group: https://ida.fbk.eu/resources

The ideal candidate is a proactive and dynamic young person with good organizational and interpersonal skills, with a propensity for teamwork, motivated to undertake a training experience in an international context.

The intern, working alongside the Research Unit staff, will mainly contribute to the development of the following activities:

Revising the existing content of FuS-KG, such as integrating recipes with nutritional information.
Extending the FuS-KG resource with new data related to health related domains, including (but not limited to) food, recipes, daily and physical activities.
Aligning FuS-KG with state-of-the-art ontologies by studying ontology matching tools and performing both automatic and manual matching.
Improving the internal Python pipeline for the materialization and population of the MMKG
Analyzing state-of-the-art deep learning models for feature extraction and incorporating features into FuS-KG nodes.

Requirements

Currently enrolled in a bachelor’s or master’s degree program in Computer Science.
Fluent in both written and spoken English (minimum level: B1).
Relational and teamwork skills;
Good adaptability, flexibility, and initiative skills;
Preferred (but not mandatory) knowledge in: Knowledge Engineering, Knowledge Graphs, Ontologies, Protégé, Python, and GitHub.

Internship Information

Internship start date: second semester 2025
Internship experience duration: minimum of 3 months, with a possible extension of an additional 3 months for thesis work.
Opportunity reserved for bachelor's/master's degree students in Computer Science
The internship experience will take place at the Science and Technology Cluster at the Povo location
We offer the possibility to use the internal canteen service

How to Apply
All interested parties are asked to fill out the online form by clicking on "Apply Online" in the "Internship opportunities" section, attaching the following documents in .pdf format:

curriculum vitae
motivational letter

Application deadline: the notice will be withdrawn when the desired applications are reached.

For any details about the internship activity, please contact: Gianluca Apriceno (apriceno@fbk.eu) and Tania Bailoni (tbailoni@fbk.eu)

For any further information, please contact the Human Resources Department at: jobs@fbk.eu

Recruitment Type	Standard
Business Unit	Centro Digital Health& Wellbeing; Centro Digital Health& Wellbeing
Locations	Science and Technology Hub - Trento