Thesis Opportunity in Advanced Machine Learning for Contact Simulation Optimization
vor 4 Wochen
Company Overview
At Robert Bosch GmbH, we are dedicated to shaping the future through innovative technologies and services that inspire and enhance the lives of individuals. Our commitment to our employees is unwavering: we grow together, we enjoy our work, and we motivate one another. Experience the difference with us.
The Robert Bosch GmbH eagerly anticipates your application.
Position Overview- Become a part of our pioneering team and collaborate with Bosch researchers to create state-of-the-art simulation tools utilized in the design and development of essential components for market applications.
- Engage with a team of researchers to gain profound insights into our proprietary simulation software for contact dynamics (EHL). Your primary focus will be enhancing our models and methodologies to boost the speed, quality, and efficiency of simulations through machine learning (ML) techniques.
- Your responsibilities will encompass the formulation of algorithms and models aimed at improving performance, scalability, and efficiency.
- Additionally, you will analyze and interpret simulation output datasets to derive significant insights for training your algorithms.
- Furthermore, you will apply machine learning methodologies, ranging from Gaussian optimization to neural networks, to construct comprehensive design models based on extensive simulation data.
- Ultimately, you will validate and showcase your enhancements on real-world design challenges.
- Education: Pursuing a Master's degree in Engineering, Computer Science, Applied Mathematics, or a related field with above-average academic performance.
- Experience and Knowledge: Proficient in programming languages such as Python; strong foundation in AI, machine learning, and optimization techniques.
- Personality and Work Ethic: A candidate with a problem-solving approach.
- Passion: Enthusiastic about programming.
- Languages: Proficient in English.
Duration: 6 months
Enrollment at a university is a prerequisite for this thesis. Please include your CV, academic transcripts, examination regulations, and, if applicable, a valid work and residence permit.
We embrace diversity and inclusion as core values within our corporate culture. Therefore, we welcome applications from all individuals, regardless of gender, age, disability, religion, ethnic background, or sexual orientation.
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