Job Description:
The Applied Mathematician contributes to engineering and architectural projects in Al Gharrafa, Qatar by developing advanced mathematical models, simulations, and analytical solutions to optimize design processes, structural behavior, system performance, and risk assessment. This role supports multidisciplinary teams by transforming complex real-world problems into solvable mathematical frameworks that improve efficiency, accuracy, and decision-making in engineering contexts.
Key responsibilities include building predictive models, conducting statistical analysis, performing numerical simulations (e.g., finite element analysis), and applying algorithms to enhance structural design, energy modeling, or construction scheduling. The mathematician also assists in interpreting big data from sensors and smart infrastructure systems, enabling data-driven solutions in smart city, transportation, and energy initiatives.
This role requires strong collaboration with engineers, architects, software developers, and planners, as well as proficiency in mathematical software and programming tools. Applied Mathematicians are critical in supporting innovation, sustainability, and resilience in modern built environments.
Job Requirement:
Education: Master’s or PhD in Applied Mathematics, Engineering Mathematics, or Computational Science.
Experience: 2–4 years applying mathematical modeling in engineering, architecture, or infrastructure-related fields.
Skills:
Proficiency in MATLAB, Python, R, or mathematical simulation tools.
Knowledge of numerical methods, optimization, and data analysis.
Experience with modeling in structural mechanics, fluid dynamics, or thermal systems.
Ability to communicate complex mathematical results to non-technical stakeholders.
Strong documentation and problem-solving skills.
Language: Fluent in English; Arabic is a plus.
Other Requirements:
Familiarity with engineering workflows and performance metrics.
Experience working on cross-disciplinary project teams.
Ability to work independently on high-complexity mathematical tasks.
Interest in smart infrastructure, automation, or AI-driven systems is advantageous.
