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Mathematical Engineer

Pubblicato il 24-08-2026 - Tenova in Arenzano

Tenova, a Techint Group company, is a worldwide partner for sustainable, innovative and reliable solutions in the metals and also through the well‑known TAKRAF and DELKOR brands in the mining industries. Tenova leverages a workforce of over 2,500 forward‑thinking professionals located in 18 countries across 5 continents, who design technologies and develop services that help companies reduce costs, save energy, limit environmental impact and improve working conditions.

Your role in Tenova: Mathematical Engineer

We are seeking a highly skilled Mathematical Engineer for the Business Unit Tenova Material Handling to apply advanced mathematical methods, modeling techniques, and computational tools to solve complex engineering and industrial problems. The ideal candidate will bridge the gap between theoretical mathematics and practical engineering applications, contributing to the design, optimization, and analysis of systems, processes, and products in the bulk material handling industry.

Key Responsibilities




- Develop and implement mathematical models and algorithms to describe and solve material handling cases
- Perform numerical simulations and computational analyses to predict system behavior and support design decisions
- Analyze complex systems using techniques from:
- differential equations
- optimization
- statistics and probability
- Design and execute model validation activities to ensure accuracy and reliability of results
- Collaborate with multidisciplinary teams (mechanical, electrical, software engineers) to integrate models into our machines
- Identify opportunities for performance improvement and cost optimization using mathematical methods
- Develop simulation tools and support R&D; activities for new technologies and products

Qualifications
- Master’s degree (MSc) in Mathematical Engineering, Applied Mathematics, Engineering (with strong mathematical background) or Physics
- Strong knowledge of mathematical modeling, numerical methods, optimization

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