Theses & Internships
Open paths into research and real-world applications
ISGroup offers opportunities for students in Computer Science and Mathematics through both internal thesis work and internships with external partners.
Activities are aligned with the group’s research directions and industrial collaborations, ranging from natural language understanding and data-centric AI to optimization and applied machine learning.
How to Apply
Interested in working with us?
Theses topics can and will evolve over time, feel free to contact us for any opportunity that fits your interests and skills, even if the specific topic is not what you are looking for.
Contacts: [TODO]
Interal Theses
Artificial intelligence
Knowledge Graph Enrichment
A Knowledge Graph is a way to represent a complex web of information via a structured graph where nodes and edges encode data in a machine-understable way.
Thesis topics in this area focus on methods for extracting, structuring, and enriching Knowledge Graphs from text through machine learning, large language models, and hybrid neuro-symbolic approaches.
Key Topics
Entity and relation extraction, semantic processing of unstructured documents, advanced information extraction problems such as discontinuous entities
artificial intelligence
Natural Language Processing & Understading
Natural Language Processing and Understanding (NLP and NLU) are recently exploded areas of research focusing on creating models able to work on human text.
Theses on NLP or NLU focus on creating and studying these models, how they read and reason about text, their similarities and differences compared to how people explore and produce natural language.
Key Topics
Model interpretability and explanability, transformer based modeling, token encoding and processing, sentence embedding
Data modeling
Data Preparation and Data-Centric AI
AI models are shaped by the data they have aviable, often to a degree underestimated by most AI research.
Theses on Data Preparation and Data Centric AI focus on bridging this gap, developing techniques to improve models with higher quality data, how to manage messy or unclean data structures, dealing with the real-world implications and biases in your training datasets.
Key Topics
Data preparation methodologies, heterogeneous and large-scale data, data quality and preprocessing pipelines, the impact of data characteristics on model performance
Optimization strategies
Multi-objective Optimization and Multi-criteria Decision Making
The field of Optimization seeks to find the best point, be it parameter configuration, model shape, production output and processes, to maximize/minimize an objective. Traditional techniques fail with multiple objectives, often working against one another.
Thesis topics in this area address computational methods for optimization and decision support in real-world, complex settings, where defining a “optimal solution” looks like is itself a non-trivial task.
Key Topics
multi-objective optimization, multi-criteria decision making, mathematical modelling for complex systems, AI methods for structured decision support
External Theses and Trainships
Artificial intelligence
Accenture – Center for Advanced AI
The Center for Advanced AI was established in 2025 through the integration of Accenture Italy’s Data & AI team with Ammagamma.
Internships are available on the study, development, and implementation of artificial intelligence techniques for the optimization of business processes and related industrial applications.
Key Topics
demand forecasting, production planning optimization, warehouse replenishment optimization, workforce scheduling, information extraction from documents, anomaly detection for machinery operation
External contats: [TODO]
Big data
Big Data in OMICs and Artificial Intelligence for Life Science
Within the collaboration with Neoralab, thesis and internship topics are available on the study and development of innovative solutions for the management and analysis of Big Data in OMICs, including multi-omics data integration, FAIR pipelines, machine learning for biomarker discovery, and tools for data exploration.
Key Topics
demand forecasting, production planning optimization, warehouse replenishment optimization, workforce scheduling, information extraction from documents, anomaly detection for machinery operation
External contats: contact@neoralab.com, fabiobove@neoralab.com
Opportunities Archive
Not interested in the broader opportunities? Here you can browse the smaller, more targeted theses and external opportunities to find something that might fit your business or academical career better.
Symbolic Regression
Internal Thesis
Methods for discovering interpretable mathematical expressions from data, with applications in scientific discovery and explainable AI.
Agentic LLMs for Manufacturing
Internal Thesis
Intelligent assistants, conversational systems, and agentic large language model architectures for industrial and manufacturing settings.
Semantic Processing of Documents
Internal Thesis
Methods for processing unstructured documents through information extraction, semantic analysis, and knowledge enrichment.
Clinical Data Preparation
Internal Thesis
Data preparation, quality assessment, and preprocessing workflows for heterogeneous clinical and biomedical datasets.
Decision Support and Optimization
Internal Thesis
Optimization and structured decision-support techniques for complex systems involving multiple and conflicting objectives.
Biomedical AI with Neoralab
External Thesis / Trainship opportunity
Applications of machine learning and AI to multi-omics integration, FAIR pipelines, biomarker discovery, and biomedical data exploration.