Linde Engineering is a global leader in the production and processing of gases, with over 4,000 successful plant references. The company combines engineering expertise with operational excellence to deliver innovative solutions across the entire plant lifecycle. Linde is committed to:
- Decarbonization & Efficiency: Offering technologies and services that support carbon abatement and energy transition.
- Hydrogen Leadership: Providing solutions across the hydrogen value chain.
- Lifecycle Support: Through LINDE PLANTSERV®, delivering reliability-enhancing services and digital innovations.
Project Goals
- Optimize project cash-out planning for third-party purchase orders across the project lifecycle by enhancing process reliability and minimizing manual intervention.
- Improve predictive accuracy of the existing cash-out curves by leveraging pattern recognition algorithms in Databricks, applied on structured historical project data.
Tasks
- Data Preparation
- Algorithm Development
- Scalability and Optimization
- Visualization and Reporting
The detailed project description, aligned with TUM requirements, will be developed in collaboration with the IPD students.
- Begin: November 2025 (Preferred start date)
- Duration: 6 months (part-time proejct)
- Supervisor ERI: Milena Barg
- Application:
- Team Size: 3–4 students
- Target Group: M.Sc. Data Engineering and Analytics program
- Documents: CV and short motivational statement
- Contact Emails: