Postdoctoral Researcher in Hybrid Machine Learning-Physics Modeling for Hydroclimatic Extremes

Décryptage du poste par Postule AI

Résumé du rôle

Postdoctoral position at Mohammed VI Polytechnic University's International Water Research Institute (IWRI) to develop hybrid machine learning-physics based modeling approaches for predicting hydroclimatic extremes in data-scarce regions, particularly Morocco. The role combines advanced machine learning with hydrological and climate modeling to address droughts and floods under limited observational data, with emphasis on translating results into actionable information for water managers and assessing long-term adaptation strategies.

Exigences clés (estimation)

Develop hybrid machine learning-physics based modeling approaches integrating data-driven algorithms with physically based hydrological and climate models
Design methods robust to data scarcity using heterogeneous data sources including remote sensing, reanalysis, and sparse in-situ observations
Detect, attribute, and predict hydroclimatic extremes under non-stationary conditions with Morocco as primary testbed
Translate model outputs into decision-relevant indicators for water resource managers and planning authorities
Assess feasibility and robustness of long-term water management strategies for mitigating water scarcity
Investigate transferability of developed methods to other data-scarce regions

Compétences

Machine learning and hybrid modeling approaches combining data-driven and physics-based methodsStrong programming skills in Python, MATLAB, Fortran or similar languages with ML frameworksExperience with hydroclimatic data including remote sensing, reanalysis datasets, and in-situ observationsAbility to develop and evaluate models under data-scarce conditionsUncertainty quantification and data assimilation techniquesCommunication skills for both scientific and non-technical stakeholders including policy actors

Niveau estimé

Postdoctoral level position requiring a PhD and demonstrated expertise in hybrid modeling, machine learning, and hydroclimatic research. Candidates should have proven ability to conduct independent research while collaborating with interdisciplinary teams and stakeholders.

Attributs détectés par l’IA (si absents de l’offre)

Type de contrat: CDD / Contrat
Mode de travail: Sur site
Niveau d'expérience: 0–1 an
Fonction: Data / BI
Secteur: Éducation
Niveau d'études: Doctorat
Langues: Anglais

Cette analyse a été générée automatiquement par Postule AI à partir de l'offre.

About the Position

The International Water Research Institute (IWRI) at Mohammed VI Polytechnic University invites applications for a postdoctoral researcher position focused on developing hybrid machine learning-physics based modeling approaches to improve understanding and prediction of hydroclimatic extremes in data-scarce regions, with primary focus on Morocco.

Key Responsibilities

Develop innovative hybrid machine learning-physics based modeling approaches that integrate data-driven algorithms with physically based hydrological and climate models under limited observations
Design and implement methods robust to data scarcity through integration of heterogeneous data sources including remote sensing, reanalysis datasets, and sparse in-situ observations
Address detection, attribution, and prediction of hydroclimatic extremes under non-stationary conditions and evaluate model performance over Morocco as primary testbed
Translate model outputs into decision-relevant indicators and actionable information for water resource managers and planning authorities
Assess feasibility and robustness of long-term water management strategies aimed at mitigating water scarcity
Investigate transferability of developed methods to other regions facing similar data-scarcity constraints

Required Qualifications

PhD in hydrology, climate science, geosciences, applied mathematics, computer science or related field
Expertise in machine learning, physically based modeling, or hybrid approaches combining both
Strong programming skills (Python, MATLAB, Fortran, or similar) and familiarity with ML frameworks
Experience with hydroclimatic data including remote sensing products, reanalysis datasets, and in-situ observations
Demonstrated ability to develop and evaluate models under data-scarce conditions
Ability to communicate results to both scientific and non-technical stakeholders including water managers and policy actors

Advantageous Skills

Knowledge of uncertainty quantification, data assimilation, or transfer learning
Proven ability to handle HPC environments

About IWRI

The International Water Research Institute provides research, education, and innovation in water and climate fields. IWRI leads integrated research and processes for Water and Climate concerns in Africa, acting as an African water hub through strategic cooperation and partnerships, focusing on integrated water resources management, climate change and adaptation, hydroinformatics, and water technologies.

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