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Thesis - Optimizing Battery Testing for EVs: Machine Learning in Lab Management, Graz
Client:
AVL List GmbH
Location:
Graz, Austria
Job Category:
Other
EU work permit required:
Yes
Job Reference:
da670e4fb0c6
Job Views:
1
Posted:
01.04.2025
Expiry Date:
16.05.2025
Job Description:
YOUR RESPONSIBILITIES:
* Analyze and adapt data models for battery testing
* Implement simple test environment to simulate battery test lab
* Analyze state of the art in ML applicable to plant management
* Select appropriate approaches and implement prototypes for tasks in the battery testing facility (allocate test equipment)
* Design an agent prototype that interacts with the environment
* Design dashboard prototypes to properly communicate necessary changes in resource allocation
YOUR PROFILE:
* Ongoing master study in the fields of Computer Science, Telematics or Physics
* Good programming skills in Python
* C# skills appreciated
* Knowledge of machine learning algorithms (reinforcement learning)
* Knowledge of data structures and translations
* Good knowledge of German and English
* Presence from time to time at our headquarter in Graz required
WE OFFER:
* You can write your thesis independently and receive professional guidance and support from our experienced employees.
* You will have the opportunity to exchange ideas with experts in the company and benefit from their expertise.
* Take the opportunity to immerse yourself in the world of AVL and embed your theoretical knowledge in a practical environment.
The successful completion of the thesis is remunerated with a one-time fee of tax.
You don't want to write your final thesis just for the books, then explore the mobility of the future together with us! Maybe you will be a part of it soon!
At AVL, we foster and celebrate diversity: We recognize that diverse ways of thinking are required to achieve our vision of a greener, safer, and better world of mobility. Different backgrounds, attitudes, interests, and experiences make us successful. As Equal Opportunity Employer we consider all qualified applicants without regard to ethnicity, religion, gender, sexual orientation or disability status.
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