V

Graduate Apprentice Trainee

VolvoBangaloreIndia1mo ago
onsitefull-timeentry
204 views142 applicants
💼 Competitive Salary

Job Description

At Volvo Group, we are driving prosperity through transport and infrastructure solutions, shaping the future of sustainable mobility. As part of our commitment to nurturing young talent, we invite fresh engineering graduates to join us under the National Apprenticeship Training Scheme (NATS). This is an excellent opportunity to gain hands-on industry experience and work alongside experts on real-world projects Eligibility Criteria Education: B.Tech / B.E. in Automobile Engineering or Mechanical Engineering Year of Graduation: 2023, 2024, or 2025/2026 Program: National Apprenticeship Training Scheme (NATS) . Key Skills & Knowledge Areas: Strong fundamentals in Strength of Materials and Solid Mechanics. Knowledge of CAE Tools such as ANSA, Hypermesh, Nastran Intermediate Knowledge of tools like Python, SQL and Data Analysis Techniques. Exposure to Data Science & AIML would be an added advantage. Statistical methods for engineering applications Passion for CAE, simulation, and engineering analytics. Interest in combining mechanical engineering with data driven decision making. Understanding of meshing, model setup, load application, boundary conditions, and result interpretation would be added advantage Roles & Responsibilities: Automate CAE workflows and simulation data processing using Python, SQL, Pandas, and NumPy to improve engineering efficiency. Analyze simulation and historical data to identify trends and enhance predictive durability methodologies. Develop dashboards and visualizations using Power BI, Tableau, Matplotlib, and Excel for engineering insights and decision making. Apply statistical analysis, predictive modelling, and basic machine learning techniques to improve durability prediction accuracy. Program Duration: As per NATS guidelines

Key Responsibilities

  • Automate CAE workflows and simulation data processing using Python, SQL, Pandas, and NumPy to improve engineering efficiency.
  • Analyze simulation and historical data to identify trends and enhance predictive durability methodologies.
  • Develop dashboards and visualizations using Power BI, Tableau, Matplotlib, and Excel for engineering insights and decision making.
  • Apply statistical analysis, predictive modelling, and basic machine learning techniques to improve durability prediction accuracy.
  • Program Duration: As per NATS guidelines

About Volvo

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