Student* with Master Thesis (optional) Tensor Decomposition for Power Systems
Fraunhofer-Gesellschaft
Who we are ...
At the Fraunhofer Institute for Wind Energy Systems IWES, the energy transition becomes a reality every day. Our focus topics are: offshore wind energy, hydrogen, test infrastructure and digitization. More than 400 employees - including around 100 students - from over 50 countries work at nine locations in scientific and non-scientific teams on the development of innovative methods to accelerate the expansion of the wind energy and hydrogen economy, minimize risks, and increase cost efficiency. Do you want to join us in shaping a sustainable future?
This team needs your support ...
You will be part of the »Application Center for Integration of Local Energy Systems« at our site in Hamburg. At present, our team consists of eight research associates and several students. We focus on the modelling and control of decentralized, local energy systems for network integration. One of our main research interests is cross-sector applications with hydrogen systems. On the control side, our current research emphasis is on grid-forming control for the integration of hybrid power plants including large-scale electrolyzes. Become an active member of the team; we are keen to hear your ideas! As an international oriented IWES-team, we highly appreciate an open exchange, whether this be in German or English. Respectful cooperation is also very important to us. You are wondering what you can bring to the team?
What you will do
These duties await you ...
Power systems keep increasing in size and complexity, posing a major modelling challenge. When dealing with truly large-scale systems, we can use approximations, like Kron reductions from graph theory. The aim is to find an approximation of the system of manageable scale while preserving its essential properties. One promising method for power system model approximation is the use of multilinear models which enable major reductions using tensor (multiarray) decomposition methods. Here you can develop model reduction routines for large-scale sparse power networks using tensor decomposition for multilinear models. You also analyse and compare the proposed multilinear tensor decomposition approaches against state-of-the-art techniques, e.g., Kron reduction, in terms of performance and accuracy.
What you bring to the table
What is your background?
Are you currently enrolled in a master's degree program studying Electrical Engineering, Control Engineering, Mathematics, or a related subject? Do you have experience in MATLAB/Simulink or Python and are you fluent in english? Are you ready to delve into mathematical problems, especially the decomposition of tensors? Great!
What you can expect
What we can offer you ...
We offer various opportunities to join us as a student. Whether it is an internship, where you gain a comprehensive insight into the areas of work, or the role of a student assistant, which is easy to combine with your studies. Are you looking for an exciting topic for your thesis and do you want to delve deeply into a topic scientifically? Together, we will find the right path for you! We know that studying can also be very demanding and requires a certain level of flexibility. That is no problem here, as - in agreement with your colleagues - you can decide flexibly what days and hours to work. Temporarily, you can even work remotely, depending on the job.
Eager to learn more?
If you would like to find out more information about the IWES, our research aspects, and your future colleagues, please visit our career website: https://s.fhg.de/5ei
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, ideology, disability, sexual orientation and identity. Severely disabled persons are given preference in the event of equal suitability.
The standard contract duration is 1 year, individual agreements are possible. The working time consists of up to 80 hours per month. Remuneration according to the general works agreement for employing assistant staff.
With its focus on developing key technologies that are vital for the future and enabling the commercial utilization of this work by business and industry, Fraunhofer plays a central role in the innovation process. As a pioneer and catalyst for groundbreaking developments and scientific excellence, Fraunhofer helps shape society now and in the future.
Interested? Apply online now. We look forward to getting to know you!
If you have any further questions, please contact:
People & Development
E-mail: personal@iwes.fraunhofer.de
Phone: +49 471 14 290-230
Only online applications via the portal can be considered.
Please note that we observe the provisions of the valid General Data Protection Regulation when processing applications.
Fraunhofer Institute for Wind Energy Systems
www.iwes.fraunhofer.de
Requisition Number: 79184 Application Deadline:
At the Fraunhofer Institute for Wind Energy Systems IWES, the energy transition becomes a reality every day. Our focus topics are: offshore wind energy, hydrogen, test infrastructure and digitization. More than 400 employees - including around 100 students - from over 50 countries work at nine locations in scientific and non-scientific teams on the development of innovative methods to accelerate the expansion of the wind energy and hydrogen economy, minimize risks, and increase cost efficiency. Do you want to join us in shaping a sustainable future?
This team needs your support ...
You will be part of the »Application Center for Integration of Local Energy Systems« at our site in Hamburg. At present, our team consists of eight research associates and several students. We focus on the modelling and control of decentralized, local energy systems for network integration. One of our main research interests is cross-sector applications with hydrogen systems. On the control side, our current research emphasis is on grid-forming control for the integration of hybrid power plants including large-scale electrolyzes. Become an active member of the team; we are keen to hear your ideas! As an international oriented IWES-team, we highly appreciate an open exchange, whether this be in German or English. Respectful cooperation is also very important to us. You are wondering what you can bring to the team?
What you will do
These duties await you ...
Power systems keep increasing in size and complexity, posing a major modelling challenge. When dealing with truly large-scale systems, we can use approximations, like Kron reductions from graph theory. The aim is to find an approximation of the system of manageable scale while preserving its essential properties. One promising method for power system model approximation is the use of multilinear models which enable major reductions using tensor (multiarray) decomposition methods. Here you can develop model reduction routines for large-scale sparse power networks using tensor decomposition for multilinear models. You also analyse and compare the proposed multilinear tensor decomposition approaches against state-of-the-art techniques, e.g., Kron reduction, in terms of performance and accuracy.
What you bring to the table
What is your background?
Are you currently enrolled in a master's degree program studying Electrical Engineering, Control Engineering, Mathematics, or a related subject? Do you have experience in MATLAB/Simulink or Python and are you fluent in english? Are you ready to delve into mathematical problems, especially the decomposition of tensors? Great!
What you can expect
What we can offer you ...
We offer various opportunities to join us as a student. Whether it is an internship, where you gain a comprehensive insight into the areas of work, or the role of a student assistant, which is easy to combine with your studies. Are you looking for an exciting topic for your thesis and do you want to delve deeply into a topic scientifically? Together, we will find the right path for you! We know that studying can also be very demanding and requires a certain level of flexibility. That is no problem here, as - in agreement with your colleagues - you can decide flexibly what days and hours to work. Temporarily, you can even work remotely, depending on the job.
Eager to learn more?
If you would like to find out more information about the IWES, our research aspects, and your future colleagues, please visit our career website: https://s.fhg.de/5ei
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, ideology, disability, sexual orientation and identity. Severely disabled persons are given preference in the event of equal suitability.
The standard contract duration is 1 year, individual agreements are possible. The working time consists of up to 80 hours per month. Remuneration according to the general works agreement for employing assistant staff.
With its focus on developing key technologies that are vital for the future and enabling the commercial utilization of this work by business and industry, Fraunhofer plays a central role in the innovation process. As a pioneer and catalyst for groundbreaking developments and scientific excellence, Fraunhofer helps shape society now and in the future.
Interested? Apply online now. We look forward to getting to know you!
If you have any further questions, please contact:
People & Development
E-mail: personal@iwes.fraunhofer.de
Phone: +49 471 14 290-230
Only online applications via the portal can be considered.
Please note that we observe the provisions of the valid General Data Protection Regulation when processing applications.
Fraunhofer Institute for Wind Energy Systems
www.iwes.fraunhofer.de
Requisition Number: 79184 Application Deadline:
JOB SUMMARY
Student* with Master Thesis (optional) Tensor Decomposition for Power Systems
Fraunhofer-Gesellschaft
Hamburg
15 days ago
N/A
Full-time
Student* with Master Thesis (optional) Tensor Decomposition for Power Systems