You develop and assess advanced AI models for analyzing system diagrams, conduct research, and collaborate with your team to showcase your results.
Anforderungen
- •Scientific subject studies
- •Interest in renewable energy research
- •Programming machine learning models in Python
- •Passion for machine learning and computer vision
- •Ability to analyze real data
- •Structured working approach
Deine Aufgaben
- •Develop and evaluate deep learning models for PI&D diagrams.
- •Use optimization methods and integrate application knowledge.
- •Research and compare your approach with current state-of-the-art techniques.
- •Prepare datasets for training and evaluating models.
- •Document results and present findings to the team.
Deine Vorteile
Exclusive insight into research
Combination of experimental work
Supervision by scientists
Experience in teamwork
Flexible working hours
Commitment to equal opportunities
After-work events
Original Beschreibung
City:
Freiburg
Date:
Jun 3, 2025
# Master thesis "Development of AI Methods for Analyzing System Diagrams"
The focus of the thesis on "Development of AI Models for Capturing Connections in System Diagrams" is the development of deep learning models to capture connections in scanned diagrams. By the end of the work, a method should be established that reliably identifies the connected components in the diagrams. You will learn about novel AI models and exchange ideas with experts from the building sector. The "Image Processing and Machine Learning" team has AI expertise and we have a high-performance IT infrastructure available.
For our "Computer Vision and Machine Learning" team, we are looking for a student assistant as soon as possible, with the opportunity to write a master's thesis.
**What you will do**
* You develop and evaluate state-of-the-art deep learning models for the inspection of PI&D diagrams.
* You use new optimization methods and combine the models with application knowledge.
* You research the state of the art and compare your approach with it.
* You prepare datasets to train and evaluate your models.
* You document your results and present them to the team.
**What you bring to the table**
* You are studying a scientific subject such as computer science, electrical engineering, engineering, materials science, renewable energies, or a comparable field.
* You are interested in renewable energy research.
* You can program machine learning models in Python.
* Machine learning methods and computer vision is part of your passion / immersion.
* You want to analyze real data and have the patience to systematically explore and analyze data.
* You are able to work in a structured way and are willing to document and present procedures, code and work results to the team.
**What you can expect**
* **Exclusive Insight:** In collaboration with the scientists of our unit, you will gain insight into the daily life of research and development at a research institute.
* **Research Mix:** You will have the opportunity to combine experimental work with theory, applying and expanding your knowledge from your studies.
* **Supervision:** You will be supervised by scientists during your work and receive feedback on your progress.
* **Teamwork:** Through interaction with scientific and student employees, you will gain experience in teamwork and can contribute your previous experiences.
* **Working Hours and Location:** We offer you the opportunity to flexibly adjust your working hours to your needs in consultation and occasionally work from home.
* **Equal Opportunities:** We value equal opportunities and provide space for diversity.
* **After Work:** Celebrate yourself and your colleagues at after-work events or our annual employee parties.
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| In addition to the thesis, a contract as a student assistant will be agreed upon. The remuneration for this will depend on the level of your academic qualification. We value and promote the diversity of our employees' skills and therefore welcome all applications—regardless of age, gender, nationality, ethnic and social origin, religion, worldview, disability, as well as sexual orientation and identity. Severely disabled persons will be given preference in case of equal suitability. |
Questions about this position can be answered by:
Antonia Hain / Matthias Demant
+49 761 4588-5651