Master's Thesis (f/m/d) Surrogate Models for the Optimization of Energy Supply Concepts

Deutsches Zentrum für Luft- und Raumfahrt e.V. · Stuttgart

ThesisGerman needed: not said

Still open on 1 Nov

You apply on the company's own website.

Key facts

Pay: Paid by a fixed pay scale (TVöD Bund)
Language needed: German and English
Subject you study: Mechanical Engineering, Process Engineering, Electrical Engineering, Computer Science, Mathematics

Research on existing approaches for data-driven surrogate models for energy systems
Selection of a methodology suitable for the use case
Implementation of the methodology in existing Python workflow
Selection of suitable data for training the surrogate model
Evaluation of the accuracy of the surrogate model and the achieved reduction in computational effort

You are studying for a master's degree in mechanical engineering, process engineering, electrical engineering, computer science, mathematics or a related field
You convince us with above-average academic achievements
You are used to working independently and responsibly and have a structured way of working
Interest and previous knowledge in Python programming and data-driven models
Good English skills are essential for reading scientific literature

DLR stands for diversity, appreciation and equality for all people. We promote independent work and the individual development of our employees in their personal and professional environment. For this purpose, our numerous training and further education opportunities are available to you. Equal opportunities are a particular concern for us; we therefore want to increase the proportion of women in science and management. Applications from severely disabled people are given preference in case of professional suitability.

Research on existing approaches for data-driven surrogate models for energy systems
Selection of a methodology suitable for the use case
Implementation of the methodology in existing Python workflow
Selection of suitable data for training the surrogate model
Evaluation of the accuracy of the surrogate model and the achieved reduction in computational effort

You are studying for a master's degree in mechanical engineering, process engineering, electrical engineering, computer science, mathematics or a related field
You convince us with above-average academic achievements
You are used to working independently and responsibly and have a structured way of working
Interest and previous knowledge in Python programming and data-driven models
Good English skills are essential for reading scientific literature

DLR stands for diversity, appreciation and equality for all people. We promote independent work and the individual development of our employees in their personal and professional environment. For this purpose, our numerous training and further education opportunities are available to you. Equal opportunities are a particular concern for us; we therefore want to increase the proportion of women in science and management. Applications from severely disabled people are given preference in case of professional suitability.