Finde einen Job 
Finde eine Ausbildung 
Top Arbeitgeber 
Top Universitäten 
Für Unternehmen Auf einen Blick
- Aufgaben: Develop a machine learning algorithm to monitor vehicle emissions and detect high emitters.
- Arbeitgeber: Join a leading automotive company focused on innovative emission solutions in Berlin.
- Mitarbeitervorteile: Earn a competitive salary while gaining hands-on experience in a cutting-edge field.
- Warum dieser Job: Contribute to environmental sustainability while enhancing your skills in machine learning and data analysis.
- Gewünschte Qualifikationen: Pursuing studies in automotive engineering or related fields; Python experience required.
- Andere Informationen: Thesis will be conducted in English, offering a unique opportunity for international collaboration.
Thesis – On-Board Monitoring with Machine Learning to Detect High Emitters
______
Students — Thesis; Limited
Berlin
The Euro 7 regulation stipulates the monitoring of vehicle tailpipe emissions in order to detect high pollutant emissions in applications with combustion engines. The on-board diagnostic system, which is already state of the art in production vehicles, is primarily designed to detect individual faults in the vehicle and provide fault codes. Combinations of deterioration mechanisms such as drift or ageing of various components may not be detected by the OBD system, but can cause an increase in tailpipe emissions.
The aim of this thesis is to develop a monitoring algorithm that uses machine learning to detect combined deviations so that additional information is available and the affected components can be replaced.
Your Tasks:
- Familiarization with the basics of combustion and exhaust gas theory of combustion engines
- Analysis and evaluation of measurement or simulation data with Python
- Machine learning with Python (e.g. autoencoder, PCA) to identify system deviations
- Visualization and validation of the results of machine learning algorithms with Python
- Optimization of the algorithm with a focus on the trade-off between complexity and accuracy
Necessary Skills:
- Current studies in a technical direction such as automotive engineering, physics
- Interest in physics, thermodynamics, computer science
- Experience in using Python
- Interest in the described field
- Independent working style and analytical thinking skills
- Good language skills in English (thesis will be in English)
Remuneration is based on our collective wage and salary agreement. The current monthly salary for this position is EUR 979. From February 2025, the monthly salary for this position will be EUR 1,012.
#J-18808-Ljbffr
Thesis - On-Board Monitoring with Machine Learning to detect High Emitters Arbeitgeber: IAV GmbH Ingenieurgesellschaft Auto und Verkehr
Kontaktperson:
IAV GmbH Ingenieurgesellschaft Auto und Verkehr HR Team
StudySmarter Bewerbungstipps 🤫
So bekommst du den Job: Thesis - On-Board Monitoring with Machine Learning to detect High Emitters
✨Tip Number 1
Make sure to familiarize yourself with the latest developments in combustion and exhaust gas theory. This knowledge will not only help you understand the context of your thesis better but also impress us during discussions.
✨Tip Number 2
Brush up on your Python skills, especially in data analysis and machine learning. Being able to demonstrate your proficiency in using libraries like Pandas, NumPy, and Scikit-learn will be a big plus.
✨Tip Number 3
Showcase any previous projects or coursework related to machine learning or automotive engineering. This will help us see your practical experience and how it aligns with the tasks outlined in the thesis.
✨Tip Number 4
Prepare to discuss your independent working style and analytical thinking skills. We value candidates who can think critically and work autonomously, so be ready to provide examples from your studies or past experiences.
Diese Fähigkeiten machen dich zur top Bewerber*in für die Stelle: Thesis - On-Board Monitoring with Machine Learning to detect High Emitters
Tipps für deine Bewerbung 🫡
Understand the Thesis Topic: Make sure to thoroughly understand the topic of the thesis, which involves on-board monitoring and machine learning for detecting high emitters. Familiarize yourself with combustion engine theory and the importance of emissions monitoring.
Highlight Relevant Skills: In your application, emphasize your current studies in a technical field, experience with Python, and any knowledge of machine learning techniques like autoencoders or PCA. Mention your analytical thinking skills and independent working style.
Tailor Your CV and Cover Letter: Customize your CV and cover letter to reflect your interest in the automotive field and the specific requirements of the thesis. Include any relevant projects or coursework that demonstrate your capabilities in data analysis and programming.
Proofread Your Application: Before submitting, carefully proofread your application materials to ensure there are no grammatical errors or typos. Since the thesis will be conducted in English, make sure your language skills are clearly demonstrated.
Wie du dich auf ein Vorstellungsgespräch bei IAV GmbH Ingenieurgesellschaft Auto und Verkehr vorbereitest
✨Understand the Basics of Combustion and Emissions
Make sure you have a solid grasp of combustion theory and exhaust gas emissions. This knowledge will not only help you answer technical questions but also demonstrate your genuine interest in the field.
✨Showcase Your Python Skills
Be prepared to discuss your experience with Python, especially in relation to data analysis and machine learning. Highlight any projects or coursework where you've used libraries like NumPy, Pandas, or Scikit-learn.
✨Discuss Machine Learning Techniques
Familiarize yourself with machine learning concepts relevant to the role, such as autoencoders and PCA. Be ready to explain how these techniques can be applied to detect system deviations in vehicle emissions.
✨Demonstrate Analytical Thinking
Prepare examples that showcase your analytical thinking skills. Discuss how you've approached problem-solving in past projects or studies, particularly in technical contexts.
