Student Assistant- Energy Grids and Machine - Munich, Deutschland - fortiss GmbH

fortiss GmbH

Geprüftes Unternehmen

Munich, Deutschland

vor 2 Tagen

Geschrieben von:

Lena Wagner

beBee Recruiter

Beschreibung

fortiss GmbH Jobportal
München, Mies-van-der-Rohe-Str. 8, fortiss GmbH (Highlight Towers)

Working student
Part time

Who are we?:

To further strengthen our Architectures and Services for Critical Infrastructures team, we are looking for a new team member:
In recent years, the landscape of energy distribution systems has undergone a remarkable transformation.

The modernization and diversification of energy networks has come with severe challenges and opportunities, and the advent of smart grids has initiated an era of massive data generation and exchange in this domain.

Data from several measuring devices distributed across the network is now available, and this together with the power of modern machine learning techniques present opportunities for a more resilient, efficient, and sustainable energy infrastructure.

The aim of the project is to develop an automated process for robust and accurate fault detection and diagnosis in low and medium-voltage grids, including load forecasting.

To this end, learning methods involving external knowledge sources must be researched for accurate and timely data-driven fault localization in medium and low voltage networks based on a digital twin.

In addition, robust approaches ensure reliable localization even when measurement data is missing or inaccurate. Our research relies on data from heterogeneous measuring devices at different locations in the grid for fault localization.

Your tasks:

Further Development of digital twins for low and medium voltage energy grids (Matlab/Simulink/Simscape)
Scaling up and parallelizing simulations and training e.g. via Cloud computing, Containerization and Virtualization Techniques (Cloud/Docker/Kubernetes/VMs)
Scripting (Python/Bash)
Developing and improving Neural Network Models for forecasting, detection and localization (Python/Pytorch/Matlab)
Code Versioning and Issue Management (Git)
Potential training and codeveloping new techniques and ML models
Networking (TCP/IP/UDP)
Potential coauthoring research papers and supporting dissemination tasks.

Your profile:

Student of B. Sc. / M. Sc. in Computer Science, Electrical Engineering or similar
Software development experience
Linux experience Desirable
Knowledge in neural networks, machinelearning
Selfmotivated and structured way of working
Good communication skills in English
German communication skills
Availability to work onsite

Our offer:

International and dynamic work environment
Flexible schedule and work in convenient location
Possibility to perform research in challenging and exciting topics in the field of machine learningand digital twins in the energy grid domain
Possibility to extend to Bachelor's or Master's thesis

Did we catch your interest?:

Job-ID:
ASCI-SH

Contact:
Camilo Amaya Rodriguez