12834 - Mid-level Researcher in Advanced Spatial Modelling of the Built Environment for Climate[...]

15 ago - Caserta
Cmcc - Centro Euro-Mediterraneo Sui Cambiamenti Climatici

CMCC Position cod. 12834 – Researcher in Advanced Spatial Modelling of the Built Environment for Climate Adaption and Resilience
Deadline: July 21, 2026
WHAT WE ARE LOOKING FOR
We seek a highly motivated and well‑organized researcher with a background in Building Information Modelling (BIM), Urban Digital Twins (UDT) and climate‑informed decision‑support systems. The ideal candidate has experience developing and applying modelling frameworks to support climate adaptation, urban regeneration, and resilience planning. The position requires expertise in urban and building‑scale modelling, scenario analysis, and the assessment of climate risks, vulnerabilities, and adaptation strategies across multiple spatial scales. The candidate should demonstrate familiarity with digital representations of the built environment, spatial analysis of buildings and infrastructure systems, and data‑driven approaches supporting climate risk and resilience assessments. Experience in climate risk assessment, urban systems modelling, decision‑support tools,



and visualization environments for policy and planning applications is considered a plus. Strong organisational skills, the ability to manage multiple priorities, and proactive engagement with interdisciplinary teams and external stakeholders are highly valued.
ROLE
The Researcher reports to the REMHI Division Director and is responsible for contributing to the development of advanced modelling and simulation approaches for assessing climate adaptation and resilience in the built environment. The role focuses on designing, developing, and applying spatial and computational modelling frameworks to represent buildings, infrastructures, and urban systems, and to evaluate their response to current and future climate stressors. The Researcher will support research and innovation activities related to urban environment modelling, scenario analysis, and performance assessment, supporting the evaluation of climate risks, vulnerabilities, and the

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