Students: Substitute models for numerical simulations based on machine learning methods

The Fraunhofer-Gesellschaft (www.fraunhofer.com) currently operates 76 institutes and research units throughout Germany and is a leading applied research organization. Around 32 000 employees work with an annual research budget of 3.4 billion euros.

The particular strength of the Fraunhofer Institute for Electronic Nano Systems ENAS lies in the development of smart systems - so-called intelligent systems for various applications. The systems combine electronic components, micro and nano sensors and actuators with interfaces for communication. Fraunhofer ENAS develops individual components, the technologies for their production as well as system concepts and system integration technologies and transfers them into practical use. Fraunhofer ENAS accompanies customer projects from the idea to the design, technology development or implementation using existing technologies, right through to the tested prototype.

Micro Materials Center (MMC) department is concerned with the reliability of electronic components. The reliability analysis of electronic component and its forecast of remaining useful life is conducted by experiment and numerical models. The aim of the application-oriented research is to replace the numerical models with surrogate models based on machine learning methods. The methods for this will be comprehensively further developed.

You are interested in the design and training of neural networks and machine learning methods in general? We can offer you exciting work as student assistant in our Micro Materials Center department starting immediately and on an ongoing basis.

What you will do

Reduction of the required data points in the training data while maintaining good prediction quality
Comparison of different network structures with regard to prediction quality
Further development of the training, validation and evaluation routines

What you bring to the table

You are an enrolled student in Chemnitz, Dresden or the surrounding area
You are enthusiastic about machine learning methods, neural networks for mapping time series and current questions of application-oriented research in this field
You have good to very good programming skills (Python, Git, OOP)
You have an independent and conscientious way of working
You are reliable, flexible and motivated
You have a very good knowledge of German or English

What you can expect

Collaboration in innovative and exciting international research projects, with the opportunity to contribute your own ideas
Professional supervision and a varied range of tasks
A collegial, pleasant and motivating working environment
Flexible working hours and thus the optimal compatibility of studies and practice

Remuneration is based on the general works agreement on the employment of support staff.

The weekly working hours must be agreed individually and may not exceed 20 hours per week for student assistants. During lecture-free periods, the agreed working hours may be higher.

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.

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 with your detailed application documents. Please enclose your certificates and a current overview of your grades with your application. Please also state when you are available and how many hours per week you would like to work.

We look forward to getting to know you!

Please address any questions you may have to
Michaela Baum
E-mail: recruiting@enas.fraunhofer.de

For data protection reasons, we can only consider applications via our career portal - thank you.

Fraunhofer Institute for Electronic Nano Systems ENAS

www.enas.fraunhofer.de

Requisition Number: 78016 Application Deadline:

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