Auf einen Blick
- Aufgaben: Develop machine learning methods for testing batteries and fuel cells.
- Arbeitgeber: AVL is a leading mobility tech company focused on innovative automotive solutions.
- Mitarbeitervorteile: Receive a one-time fee of EUR 3,500 and professional guidance during your thesis.
- Warum dieser Job: Immerse yourself in cutting-edge technology and collaborate with industry experts.
- Gewünschte Qualifikationen: Ongoing studies in Computer Science, Physics, or Electrical Engineering; programming skills in Python or C++ required.
- Andere Informationen: Presence at our Graz headquarters is mandatory for this thesis opportunity.
We offer the following reserach topic: Thesis – Machine learning based testing of battery and fuel cells Your Responsibilities Fitting Physical Models to the test measurements of the Batteries or Fuel Cells are a powerful tool in capturing their inner characteristics. However, the fidelity of the physical model is highly dependent on the set of physical phenomena coved by mathematical formalism. Differently, testing based on data-driven models, like artificial neural networks (ANN) does not require the use of prior electrochemical knowledge and their inference relies entirely on the data collected during the testing. Although such data-driven models can be very accurate, they also require a large training dataset and do not generalize well outside the training data domain. Development of machine learning methods Implementation of the developed methods into AVL testing pipeline of Batteries and Fuel Cells Overcoming limitations of sparse and out-of-distribution training datasets Your Profile Ongoing studies in the fields of Computer Science, Telematics, Physics or Electrical Engineering Good programming skills in Python or C++ Knowledge of Machine Learning Good knowledge of German and English Skills in solving PDE are beneficial For this thesis is your presence 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. About AVL AVL is one of the world’s leading mobility technology companies for development, simulation and testing in the automotive industry, and beyond. The company provides concepts, solutions and methodologies in fields like vehicle development and integration, e-mobility, automated and connected mobility (ADAS/AD), and software for a greener, safer, better world of mobility. The successful completion of the thesis is remunerated with a one-time fee of EUR 3.500,– before 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! Apply now AVL is not just about cars. It\’s about changing the future. Together.
AVL List GmbH | Thesis - Machine learning based testing of battery and fuel cells Arbeitgeber: AVL LIST GmbH
Kontaktperson:
AVL LIST GmbH HR Team
StudySmarter Bewerbungstipps 🤫
So bekommst du den Job: AVL List GmbH | Thesis - Machine learning based testing of battery and fuel cells
✨Tip Number 1
Make sure to highlight any relevant projects or coursework related to machine learning and battery technology during your discussions. This will show your practical understanding and enthusiasm for the topic.
✨Tip Number 2
Familiarize yourself with AVL's current projects and technologies in the field of e-mobility. Being able to discuss these during your interview will demonstrate your genuine interest in the company and its mission.
✨Tip Number 3
Brush up on your programming skills, especially in Python or C++. Be prepared to discuss how you have used these languages in past projects or coursework, as this is crucial for the role.
✨Tip Number 4
Since good knowledge of German is required, practice discussing technical topics in German. This will help you feel more confident during the interview and show that you are ready to communicate effectively in the workplace.
Diese Fähigkeiten machen dich zur top Bewerber*in für die Stelle: AVL List GmbH | Thesis - Machine learning based testing of battery and fuel cells
Tipps für deine Bewerbung 🫡
Understand the Research Topic: Make sure to thoroughly understand the research topic related to machine learning and testing of batteries and fuel cells. Familiarize yourself with the concepts of physical models, data-driven models, and the specific challenges mentioned in the job description.
Highlight Relevant Skills: In your application, emphasize your ongoing studies in Computer Science, Telematics, Physics, or Electrical Engineering. Clearly showcase your programming skills in Python or C++, as well as your knowledge of machine learning.
Craft a Strong Motivation Letter: Write a motivation letter that reflects your passion for the field and your desire to work on innovative projects at AVL. Mention how your academic background and skills align with the responsibilities outlined in the job description.
Proofread Your Application: Before submitting your application, carefully proofread all documents to ensure there are no grammatical errors or typos. Make sure your German and English language skills are clearly demonstrated in your CV and motivation letter.
Wie du dich auf ein Vorstellungsgespräch bei AVL LIST GmbH vorbereitest
✨Showcase Your Programming Skills
Make sure to highlight your programming skills in Python or C++. Be prepared to discuss specific projects or experiences where you utilized these languages, especially in the context of machine learning or data analysis.
✨Demonstrate Your Knowledge of Machine Learning
Since the thesis involves machine learning methods, be ready to explain key concepts and techniques. Discuss any relevant coursework or projects that involved artificial neural networks or data-driven models.
✨Prepare for Technical Questions
Expect technical questions related to physical models, testing methodologies, and the challenges of working with sparse datasets. Brush up on your understanding of these topics to confidently address any inquiries.
✨Communicate Effectively in German and English
Given the requirement for good knowledge of both German and English, practice discussing your research interests and technical concepts in both languages. This will demonstrate your communication skills and adaptability.