24 часа назад
Working Student (m/f/d) - Production/Petroleum Engineering
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Описание вакансии
Текст:
TL;DR
Working Student (m/f/d) - Production/Petroleum Engineering (Python/AI): Developing data-driven optimization solutions for gas-lift operations, production allocation, and full-field production performance with an accent on pipeline-network effects, operational constraints, and production-flow prediction. Focus on improving gas-lift design, virtual metering, nodal-analysis tools, and the automation and validation of engineering data.
Location: Wietmarschen-Lohne, Germany; 100% remote working possible
Part-time position for 12–20 hours per week.
Company
develops sensor-based and cloud software solutions for more efficient energy production.
What you will do
- Support data-driven optimization solutions for gas-lift operations, production allocation, and full-field production performance.
- Contribute to models and algorithms covering pipeline-network effects, operational constraints, and well–reservoir interactions.
- Improve gas-lift design, injection-depth optimization, and production-flow prediction.
- Further develop virtual-metering and nodal-analysis tools for estimating production rates from operational data.
- Automate, validate, and quality-assure engineering and operational data used in optimization workflows.
- Translate production-engineering challenges into practical, scalable software solutions with an interdisciplinary team.
Requirements
- Currently pursuing a Master’s degree in Petroleum Engineering, Production Engineering, or a comparable field.
- Solid programming skills in Python.
- Confident communication in English.
- Structured, independent working style and ability to collaborate in an agile, interdisciplinary team.
Nice to have
- Experience with production-system and pipeline-network simulation tools such as PROSPER, GAP, or PIPESIM.
Culture & Benefits
- Meaningful involvement in projects and practical insight into the work.
- Mentoring and support from an experienced team.
- Supportive environment for professional development.
- Agile, autonomous, and interdisciplinary collaboration.
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