- HOSTING
- Italy
Hosting Information
- Offer Deadline
- EU Research Framework Programme
- Horizon Europe - MSCA
- Country
- Italy
- City
- Pisa
Organisation/Institute
- Organisation / Company
- University of Pisa
- Department
- Department of Civilizations and Forms of Knowledge
- Laboratory
- MAPPA Lab
- Is the Hosting related to staff position within a Research Infrastructure?
- No
Contact Information
- Organisation / Company Type
- Higher Education Institution
- Website
- gabriele.gattiglia@unipi.it
- State/Province
- Italy
- Postal Code
- 56126
- Street
- Via Paoli 15
- Phone
Description
This research project explores how Artificial Intelligence can transform archaeological data analysis, focusing on innovative methods in Digital Archaeology and spatial modelling. It encompasses various facets, including but not limited to:
- Data Analysis and Spatial Analysis: The project will address the collection, organisation, and interpretation of archaeological datasets at multiple scales (e.g. site-level excavation records and regional survey data). Candidates will apply statistical modelling, machine learning, and spatial interpolation techniques across diverse chronological contexts.
- AI Application in Archaeology: We encourage applications that engage with novel AI methods—such as representation learning, transfer learning, or self-supervised models—to address specific challenges like incomplete datasets, classification tasks, or automated pattern recognition in material culture. In addition to technical innovation, projects are expected to reflect on the ethical implications of using AI in archaeology, including issues of bias in datasets, the risk of decontextualisation, and the responsible communication of algorithmic interpretations to both academic and public audiences.
An emphasis will be placed on the open dissemination of results, aligning with FAIR data principles and open science frameworks.
Hosting Lab
MSCA Postdoctoral Fellows will be hosted at the MAPPA Lab (https://www.mappalab.eu/en/home-eng/), a leading research unit within the Department of Civilizations and Forms of Knowledge at the University of Pisa. The Lab is internationally recognised for its contributions to Digital Archaeology and AI-driven research. It offers an interdisciplinary and stimulating environment, bringing together archaeologists, data scientists, and computer scientists working on projects spanning from prehistoric to contemporary archaeology.
The MAPPA Lab supports the full archaeological data lifecycle—from acquisition to publication as open data—with particular expertise in big data management, statistical analysis, and AI applications. It organises two international training schools: R4aRchaeologists (Winter School on Statistical Analysis with R) and Neural Networks for Archaeologists (Winter School on AI with Python).
MAPPA has led pioneering projects such as the H2020 ArchAIDE (ARCHaeological Automatic Interpretation and Documentation of cEramics, 2016-2019), dedicated to automated pottery recognition using AI, and doctoral projects on robotics and generative AI. Starting in September 2024, it coordinates the Horizon Europe RIA project AUTOMATA (AUTOMated enriched digitisation of Archaeological liThics and cerAmics) https://automata-eccch.eu/, which integrates AI-augmented robotics and sensors to generate 3D models enriched with archaeometric data, enhancing AI-human collaboration in field data collection.
Supervisor
Gabriele Gattiglia is an associate professor of archaeological methods and theory at the University of Pisa, where he coordinates the MAPPA lab. His research focuses on digital archaeology and artificial intelligence, particularly in relation to post-medieval and contemporary contexts. He coordinates the winter schools 'R4aRchaeologists' and 'Neural Networks for Archaeologists, with Python, ' and has coordinated the H2020 ArchAIDE project. Additionally, he is the principal investigator for the Horizon Europe project AUTOMATA. Gattiglia serves as the Chair of the COST Action MAIA (Machine Learning and Artificial Intelligence in Archaeology) and is a team member of the ERC-funded project AviArch (Avifauna in Archaeological Network, https://www.mappalab.eu/en/aviarch-eng/ ). He contributes to the FAIR (Future of AI Research) project under the Italian Next Generation EU programme and sits on the Scientific Committee of the Computer Applications in Archaeology (CAA) Association. Currently, he supervises eight PhD students, three of whom are focused on AI in archaeology. With extensive field experience and over 100 published articles, he is recognised as an authority in methodological innovation and digital approaches in archaeology. As a supervisor, he supports interdisciplinary, critical, and forward-thinking research proposals.
Eligibility criteria
Applicants must have a PhD degree at the time of the deadline for applications (10th September 2025). Applicants who have successfully defended their doctoral thesis but who have not yet formally been awarded the doctoral degree will also be considered eligible to apply.
At the call deadline, the applicant must have a maximum of 8 years experience in research, from the date of the award of their PhD degree. Years of experience outside research and career breaks will not count towards the above maximum, nor will years of experience in research in third countries, for nationals or long-term residents of EU Member States or Horizon Europe Associated Countries who wish to reintegrate to Europe.
Mobility Rule: The applicant may be of any nationality (European Fellowships) or nationals or long-term residents of EU Member States or Horizon Europe Associated Countries (Global Fellowships) but must not have resided or carried out their main activity (work, studies, etc.) in Italy (for European Fellowships) or the host organisation for the outgoing phase (in case of Global Fellowship) for more than 12 months in the 3 years immediately before 10th September 2025.
Application procedure
Expressions of interest must be sent by email to gabriele.gattiglia@unipi.it no later than May 15th, 2025 (23.59 CEST) and must consist of two pdf files:
- Complete and updated CV, clearly demonstrating all 3 eligibility requirements.
- Motivation letter, maximum one page.