PhD Position – Energy Systems Models: The Institute of Climate and Energy Systems – Jülich System Analysis (ICE-2) is offering a PhD position focusing on developing AI-driven methods for integrating and automating heterogeneous energy research data into energy systems models. This position is part of a national project covering innovative solutions for sustainable energy systems research, emphasizing transparency, reproducibility, and scalability.
PhD Position – AI-driven Integration of Heterogeneous Research Data into Energy Systems Models
Designation
PhD Candidate
Table
| Category | Details |
|---|---|
| Position | PhD Position in AI-Driven Energy Systems |
| Organization | Institute of Climate and Energy Systems, Jülich – ICE-2 |
| Location | Jülich, Germany |
| Level | Doctoral (PhD) |
| Field of Research | AI, Energy Systems Modeling, Big Data |
| Funding | Pay in line with 75% of pay group 13 under Collective Agreement for Public Service (TVöD-Bund) with additional benefits |
Research Area
Development and integration of AI-driven methodologies to automate and process heterogeneous research data for sustainable energy systems modeling. Specific focus includes:
- Application of FAIR and Linked Open Data principles.
- Knowledge graph development for transparent energy research workflows.
- Methods to enhance data/software interoperability for automated reuse.
Location
Jülich, Germany – One of the largest and most renowned research hubs in Europe, known for its interdisciplinary and international academic environment.
Eligibility/Qualifications
- Educational Background: Master’s degree in computer science, data science, natural sciences, economics, engineering, mathematics, or related fields.
- Skills:
- Basic knowledge of AI and data analysis methods.
- Programming skills (preferred: Python).
- Independent and analytical working style.
- Fluent written and spoken English (German skills are advantageous).
- Interest: Strong enthusiasm for data science and energy technology.
Position Description
The selected candidate will:
- Develop techniques to automate the integration and semantic enrichment of energy systems data.
- Create structured, machine-readable formats for software interfaces and data models.
- Apply state-of-the-art AI technologies for organizing research data.
- Collaborate with stakeholders to enhance software interoperability.
- Support scalable and transparent workflows for open-source energy systems modeling.
- Utilize innovative knowledge graphs to ensure sustainability and expandability of energy and software assets.
Your team will provide professional supervision and ensure timely completion of the PhD thesis (within ~3 years).
How to Apply
Follow these steps to apply for this exciting opportunity:
- Visit the application portal here (applications via email are not accepted).
- Prepare all relevant documents (e.g., academic CV, cover letter, proof of qualifications).
- Submit your application as soon as possible, as the position remains open until filled.
For additional questions, refer to the FAQs on the application page or use the contact form.
Last Date to Apply
The position remains open until successfully filled. Early applications are strongly encouraged.
Why Join?
The successful applicant will benefit from:
- Membership in a motivated and interdisciplinary team dedicated to energy research.
- Access to state-of-the-art infrastructure for scientific activities.
- Opportunities to work flexibly in a supportive academic environment.
- Competitive remuneration and additional special payments (e.g., Christmas bonus).
- 30 days of annual leave and work-life balance initiatives.
- Professional guidance during the doctoral process.
Start your academic career in a meaningful field shaping the future of sustainable energy. Apply today!
