At the Institute of Climate and Energy Systems - Energy Systems Engineering (ICE-1) we focus on the optimal design and operation of integrated, decentralized energy systems with a high share of renewable energy.
Your Job:
- Development of a one-dimensional physics-informed neural network (1D PINN) to model liquid–liquid separation processes
- Integration of the 1D PINN model into an existing state-estimation framework
- Extension of existing 0D lumped PINN and mechanistic models and direct comparison with these approaches
- Investigation of different separation geometries and analysis of how temperature, phase fraction, and phase heights influence separation efficiency
- Access to a 1D mechanistic model for generating synthetic data
- Availability of experimental data from a gravity settler provided by a partner institute
- Supervision from both chemical engineering and machine learning experts, ensuring strong interdisciplinary guidance
Table of Content
Summary
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Benefits
- PRACTICAL RELEVANCE: With us, you will gain valuable practical experience alongside your studies and actively participate in interdisciplinary projects
- ONBOARDING & TEAMWORK: You can look forward to working in a dedicated, international, and collegial team. It is important to us that you quickly settle into the team and are given structured training for your tasks. We also support you from the very beginning and make your start easier with our Welcome Days and Welcome Guide: https://go.fzj.de/welcome
- SCIENTIFIC ENVIRONMENT: You can expect excellent scientific equipment, modern technologies, and qualified support from experienced colleagues
- SUPPORT: Qualified support through your scientific colleagues
- PERSONAL RESPONSIBILITY: You organize your tasks independently—from preparation to implementation
- FLEXIBILITY: Flexible working hours make it easier for you to balance work and study
- FAIR REMUNERATION: We will pay you a reasonable remuneration for your thesis
- CAMPUS EXPERIENCE: Our research campus in the countryside creates ideal conditions for collegial exchange and sporting activities right on site. Our cafeteria offers a wide range of options—you can enjoy a relaxing lunch break with a lake view
Requirements
- Current Master`s student in Process Systems Engineering, Computational Engineering Science, Chemical Engineering or a comparable course of study
- Previous experience with programming in Python
- Experience in modeling, simulation or machine learning
- Fluent / good knowledge of written and spoken English
- High degree of independence, motivation and reliability / independent and analytical working style
- Very reliable and conscientious style of working
- Excellent ability to cooperate and work in a team
Application Deadline
Not SpecifiedHow To Apply
Are you qualified and interested in this opportunity? Kindly go to
Forschungszentrum Jülich on www.fz-juelich.de to apply
For more information, kindly visit FZ Julich scholarship webpage.
