The research project (entitled PHOENIX) that the PhD candidate is going to pursue will be funded by the Concerted Research Action program of the University of Namur. PHOENIX is a highly collaborative and interdisciplinary project in the field of Cultural Heritage Sciences, which brings together PIs of the Namur Institute of Structured Matter (NISM), the Namur Institute for Complex Systems (naXys) and the Institute Heritages, transmissions & inheritances institute (PaTHs). The project focuses on two types of cultural heritage objects: parchments and coins. PHOENIX aims to develop a methodology based on physicochemical characterizations capable of addressing common objectives for these radically different artefacts. Three objectives will be the determination of date, provenance, and production chain of both artefacts by experimental techniques combined with automated machine learning procedures. The next objective will be to examine to which extent the results obtained by AI challenges existing methods used in historical sciences. Five complementary techniques (µ-Raman, UV/Vis/NIR, ATR-FTIR, IBA, ToF-SIMS) will be used to characterize the artefacts, with a fine tuning of the experimental parameters depending on the type of object. The measurements from each technique will be first analyzed (i.e., pre-screening) to obtain a physicochemical interpretation of the raw data. Then, these pre-screened datasets will be analyzed by various machine learning methods (dimensionality reduction, unsupervised clustering, artificial neural networks). The overall objective will be a critical assessment of the contribution of AI to historical studies, possibly showcasing the emergence of new paradigms in history. The PhD student will develop his/her research project in the material analysis of parchments and coins. She/he will be trained into the main analytical techniques mentioned above, will carry out the experimental measurements on the artefacts, analyze and interpret the experimental data and interact with two postdoctoral researchers who will be hired on the project, one researcher with expertise in AI who will develop the algorithms, and one researcher in historical sciences who will take in charge the interpretation of the results from an historian’s perspective.
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