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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Postdoctoral Researcher in Archaelogy and AI - **Company:** Vub - **Location:** Brussel, Belgium (Remote available) - **Experience:** Experienced - **Contract:** Temporary contract - **Skills:** Artificial Intelligence, Databases, Digital Data, Machine Learning, Reinforcement Learning, Data Layers, Information Technology - **Published:** August 1, 2026 - **Apply:** https://www.careerjet.be/jobad/be323bbdf8170e918d308a0970b03ee107 ## About the Role * Experience with computing, preferably machine learning; candidates from an archaeological background with a strong willingness to develop AI/ML skills are also encouraged to apply, and vice versa * Highly motivated to cross the boundaries between humanities and sciences and to work within a multidisciplinary team * Strong scientific track record in relation to your seniority * Experience writing or contributing to successful research grant proposals * Excellent digital data management skills (e.g. database creation, spatial analysis/GIS) * Team spirit and excellent communication skills * Strong proficiency in English (oral and written) * You stayed abroad for at least 12 months of the 3 years preceding the start date, and during this period you did not work or study in Belgium. However, during these 12 months, short-term stays in Belgium are allowed such as holidays, participation in conferences or a short stay to prepare your stay as a postdoctoral researcher. * As a (non-)EEA national, meet the conditions for obtaining a valid permit for VUB and comply with the VUB residence requirements. More info, Research Field Computer science Years of Research Experience 4 - 10 Research Field Environmental science Years of Research Experience 4 - 10 Research Field History Years of Research Experience 4 - 10 ## Description The Faculteit Letteren en Wijsbegeerte, Department History, Archeology, Arts, Philosophy and Ethics, Research Group Archaeology, Environmental changes and GeoChemistry is looking for a postdoctoral researcher with a grant. Join the VUB AMGC team (Archaeology, Environmental changes and Geo-Chemistry) and the FLAIR research group (Federated Labs AI and Robotics) for the ARCHAI project, which explores the crossover between artificial intelligence and Archaeological Prospection. Archaeological prospection faces an unusual combination of challenges: data are sparse and unevenly distributed, observations are uncertain, and decisions about where to survey unfold sequentially under significant time and cost constraints. Existing predictive models provide useful but incomplete support because they cannot fully capture the complexity and heterogeneity of archaeological data. This underscores the need for approaches that explicitly capture uncertainty, adapt dynamically to new information, and sequentially optimise survey strategies in a transparent and robust manner. ARCHAI, a new fully funded interdisciplinary research project of the VUB, introduces a new research framework that treats archaeological prospection as a sequential decision-making process explored through computational simulation and deep multi-objective reinforcement learning. The project will investigate a simulation platform that reproduces the structure of real prospection activities by integrating multiple, heterogeneous geospatial and archaeological data layers. Within this environment, we will design and evaluate new reinforcement learning algorithms capable of operating in large, partially observed spatial domains to infer efficient, interpretable strategies for estimating archaeological potential, that capture distinct criteria including scientific yield and cost effectiveness. These strategies will then be tested in real field settings (e.g. Turkey, Cyprus and Flanders) to assess how well simulation-trained decision policies transfer to practical archaeological contexts. The initiative combines the AMGC group's extensive expertise in archaeological prospection with the FLAIR's strengths in developing new multi-objective deep reinforcement learning algorithms, to support decision makers under uncertainty. VUB team:Prof. dr. Ralf Vandam (AMGC), Prof. dr. Pieter Libin (FLAIR) Within the ARCHAI project, you will coordinate the collaboration between the archaeological (AMGC) and AI (FLAIR) teams, contributing to the development of a simulator of real-world archaeological search processes and to the AI methods that learn effective discovery strategies within it. You will combine archaeological and landscape data (maps, satellite imagery, archaeological datasets) with machine learning approaches to build a system that highlights promising locations for archaeological research. You are also expected to play an active role in project coordination and in writing follow-up grant applications to expand the research. Your key responsibilities: * Co-coordinate the ARCHAI project, ensuring close collaboration between the AMGC and FLAIR teams * Contribute to the development of machine learning methods for archaeological predictive modelling / site discovery * Contribute to the design of the archaeological search-process simulator used to train and evaluate AI methods * Write grant applications to extend and expand this line of research * Take an active part in AMGC and FLAIR activities (attend regular meetings) and work closely with all members of both teams (PIs, PhDs, and postdocs) * (Help with) supervising MSc and BSc theses related to the project * Synthesize and publish results in peer-reviewed journal articles and computer science conferences * Present results to academic and policy audiences at meetings, forums, workshops and conferences * Promote and communicate the project's results through outreach activities aimed at the general public For this function, our Brussels Humanities, Sciences & Engineering Campus (Elsene) will serve as your home base. 3 - Profile What do we expect from you? * A PhD in archaeology or computer science/AI, or a related discipline ## Related Videos - [Kubernetes and Microservices with Multi-Model Databases](https://www.wearedevelopers.com/videos/382-kubernetes-and-microservices-with-multi-model-databases) - [Why Your AI Agent Keeps Hallucinating Your Data: Building Deterministic Context Layers](https://www.wearedevelopers.com/videos/2055-why-your-ai-agent-keeps-hallucinating-your-data-building-deterministic-context-layers) - [Harnessing the Power of Open Source's Newest Technologies](https://www.wearedevelopers.com/videos/1448-harnessing-the-power-of-open-source-s-newest-technologies) - [AI, DEI & Community: What’s Next for Talent Acquisition in 2025?](https://www.wearedevelopers.com/videos/1315-ai-dei-community-what-s-next-for-talent-acquisition-in-2025) - [Fault Tolerance and Consistency at Scale: Harnessing the Power of Distributed SQL Databases](https://www.wearedevelopers.com/videos/1146-fault-tolerance-and-consistency-at-scale-harnessing-the-power-of-distributed-sql-databases) - [Unlocking the potential of Digital & IT at Vodafone](https://www.wearedevelopers.com/videos/602-unlocking-the-potential-of-digital-it-at-vodafone) ## Related Articles - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [How to Find Tech Jobs in Amsterdam](https://www.wearedevelopers.com/magazine/279-how-to-find-tech-jobs-in-amsterdam) - [How to land a developer job in Amsterdam](https://www.wearedevelopers.com/magazine/36-how-to-land-a-developer-job-in-amsterdam) - [Dev Digest 121 - AI goes offline](https://www.wearedevelopers.com/magazine/456-dev-digest-121-ai-goes-offline) - [The Most Popular IT Jobs on the Market](https://www.wearedevelopers.com/magazine/376-the-most-popular-it-jobs-on-the-market) - [How to Find Tech Jobs in Vienna](https://www.wearedevelopers.com/magazine/292-how-to-find-tech-jobs-in-vienna)