At Climate Lead Group we are looking for a specialist to support the technical development of physical damage functions (fragility curves), in a role that combines physical vulnerability engineering of road infrastructure with statistical and computational modelling.
Contract type: product-based consultancy, approximately 8 months, remote.
We are looking for a person with:
- Civil, structural, geotechnical or related engineering background
- At least 8 years of experience in vulnerability, fragility or physical damage of infrastructure
- Demonstrable experience working with fragility curves (HAZUS/SYNER-G), applied statistics and scientific programming (Python/R)
- Desirable: knowledge of Bayesian methods and multi-hazard approaches
The selected consultant will be responsible for supporting:
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Definition for each road asset (bridges, road segments and pavements, culverts and drainage, embankments, cuts, slopes, retaining walls and tunnels) of a typology catalogue and an operational and observable definition of damage states DS0–DS4, based on HAZUS and SYNER-G, adapted to regional construction practice (SIECA/JICA manuals).
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Selection and justification of intensity measures by hazard: earthquake (PGA, PGV), flooding and scour (flow depth, velocity, scour depth), rainfall and landslide (intensity and duration), and coastal and tsunami hazards (flow depth, velocity, hydrodynamic force).
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Construction of lognormal fragility functions, P(DS ≥ ds | IM), fitted by maximum likelihood or least squares, ensuring consistency across damage states (no curve crossing) and compatibility with HAZUS/SYNER-G.
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Coherent integration of empirical, analytical and hybrid approaches, anchoring the curves in reference analytical and empirical evidence and regional historical records (DESINVENTAR, CEPAL reports).
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Conversion of fragility curves into mean damage ratios, from HAZUS reference values adjusted to the regional cost context.
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Uncertainty quantification through Monte Carlo simulation and Latin Hypercube sampling, reporting P5/P50/P95 bands, and prioritisation of dominant parameters through sensitivity analysis (Sobol indices).
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Calibration of the curves against historical events through Bayesian updating, evaluating performance before and after adjustment.
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Packaging the validated vulnerability functions in open formats (CSV/JSON), with metadata and a data dictionary.
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Rigorous documentation of assumptions, parameters and methodological decisions, and contribution to systematic literature review and quality assurance (QA/QC) of technical outputs.
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General project management, including: stakeholder management, organisation of key meetings, systematisation of agreements, preparation of progress and results reports, among others.
Send your CV to hr@clg-cr.com before Friday, 25 September.