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- Aufgaben: Work on cutting-edge machine learning models for virtual sensors in e-bikes.
- Arbeitgeber: Join Bosch, a leader in innovative technologies that enhance lives.
- Mitarbeitervorteile: Gain hands-on experience and collaborate with experts in a supportive environment.
- Warum dieser Job: Contribute to the future of smart e-bikes while developing your skills in a dynamic team.
- Gewünschte Qualifikationen: Master's students in relevant fields with machine learning and Python skills are encouraged to apply.
- Andere Informationen: Diversity is key at Bosch; all backgrounds are welcome!
Company Description
At Bosch, we shape the future by inventing high-quality technologies and services that spark enthusiasm and enrich people’s lives. Our promise to our associates is rock-solid: we grow together, we enjoy our work, and we inspire each other. Join in and feel the difference.
The Robert Bosch GmbH is looking forward to your application!
Job Description
- During your master thesis you will apply and adapt state-of-the-art sequence models from recent publications in the field of machine learning, in the context of virtual sensors for the smart and safe e-bike of the future.
- You will train and compare models to assess their suitability and performance, while experimenting with the training scheme.
- Ideally a demonstrator of the final approach will be realized to validate the functionality.
Qualifications
- Education: master studies in the field of Computer Science, Artificial Intelligence, Mechatronics, Electrical Engineering, Cybernetics or comparable with good grades.
- Experience and Knowledge: in the field of machine learning; good Python programming skills; practical experience with ML libraries like PyTorch or TensorFlow and neural network training; ideally first experiences with sequence models (LSTMs, GRUs, transformers, …); knowledge in the fields of state estimation and vehicle dynamics are an advantage.
- Personality and Working Practice: motivated to try out and learn new things with an independent and systematic approach to the task.
- Languages: fluent in English or German.
Additional Information
Start: according to prior agreement
Duration: 6 months
Requirement for this thesis is the enrollment at university. Please attach your CV, transcript of records, examination regulations and if indicated a valid work and residence permit.
Diversity and inclusion are not just trends for us but are firmly anchored in our corporate culture. Therefore, we welcome all applications, regardless of gender, age, disability, religion, ethnic origin or sexual identity.
Need further information about the job?
Alessandro Moia (Functional Department)
+49 711 811 43672
Silas Klug (Functional Department)
+49 711 811 8344
#J-18808-Ljbffr
Thesis in Machine Learning Based Virtual Sensor for eBikes Arbeitgeber: Bosch Group
Kontaktperson:
Bosch Group HR Team
StudySmarter Bewerbungstipps 🤫
So bekommst du den Job: Thesis in Machine Learning Based Virtual Sensor for eBikes
✨Tip Number 1
Familiarize yourself with the latest research in machine learning, especially focusing on sequence models like LSTMs and transformers. This will not only help you understand the current trends but also give you a solid foundation to discuss your ideas during the interview.
✨Tip Number 2
Get hands-on experience with ML libraries such as PyTorch or TensorFlow. Consider working on small projects or contributing to open-source initiatives that utilize these tools, as practical knowledge can set you apart from other candidates.
✨Tip Number 3
Prepare to demonstrate your problem-solving skills by thinking of potential challenges in developing virtual sensors for e-bikes. Be ready to discuss how you would approach these challenges and what innovative solutions you might propose.
✨Tip Number 4
Network with professionals in the field of machine learning and e-mobility. Attend relevant workshops or webinars, and don’t hesitate to reach out to current or former Bosch employees on platforms like LinkedIn to gain insights about the company culture and expectations.
Diese Fähigkeiten machen dich zur top Bewerber*in für die Stelle: Thesis in Machine Learning Based Virtual Sensor for eBikes
Tipps für deine Bewerbung 🫡
Understand the Company: Familiarize yourself with Bosch and their commitment to innovation and technology. Highlight how your values align with their mission in your application.
Tailor Your CV: Make sure your CV reflects your education and experience relevant to machine learning, Python programming, and any practical work with ML libraries. Emphasize your skills in sequence models if applicable.
Craft a Strong Cover Letter: Write a cover letter that showcases your motivation for the thesis position. Discuss your interest in e-bikes and how your background makes you a suitable candidate for this role.
Prepare Required Documents: Gather all necessary documents such as your CV, transcript of records, examination regulations, and any permits if required. Ensure everything is up-to-date and clearly presented.
Wie du dich auf ein Vorstellungsgespräch bei Bosch Group vorbereitest
✨Showcase Your Machine Learning Knowledge
Be prepared to discuss your understanding of machine learning concepts, especially sequence models like LSTMs and GRUs. Highlight any relevant projects or coursework that demonstrate your expertise in this area.
✨Demonstrate Your Programming Skills
Since good Python programming skills are essential for this role, be ready to talk about your experience with Python and ML libraries such as PyTorch or TensorFlow. If possible, share examples of code you've written or projects you've completed.
✨Express Your Motivation to Learn
Bosch values a motivated and independent approach to work. Share instances where you took the initiative to learn something new or tackled a challenging problem on your own. This will show your enthusiasm for the field.
✨Prepare Questions About the Role
Having thoughtful questions prepared shows your interest in the position and the company. Ask about the specific challenges they face in developing virtual sensors for e-bikes or inquire about the team dynamics and culture at Bosch.
