Aktuelle Jobs im Zusammenhang mit Thesis - LLM-based Automated Root-Cause Analysis for Unexpected System Behavior - Graz, Steiermark - AVL List GmbH
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Graz, Steiermark, Österreich AVL List GmbH VollzeitWe present an exciting research opportunity:Thesis: LLM-Based Automated Root-Cause Analysis for Unexpected System BehaviorYour ResponsibilitiesWe are looking for a dedicated student to undertake a master's thesis focused on LLM-based automated root-cause analysis within the automotive sector. Your role will involve developing methodologies to assess...
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Graz, Steiermark, Österreich AVL List GmbH VollzeitWe present an exciting research opportunity:Thesis: LLM-based Automated Root-Cause Analysis for Unexpected System BehaviorYour ResponsibilitiesWe are in search of a dedicated student to undertake a master's thesis focused on LLM-based Automated Root-Cause Analysis within the automotive sector. Your role will involve the development of methodologies to...
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Thesis - LLM-based Automated Root-Cause Analysis for Unexpected System Behavior
vor 3 Monaten
YOUR RESPONSIBILITIES:
- Compile information from various sources (FP-sheets, technical reports, presentations, word documents) to establish a knowledge base.
- Design the database structure to streamline the processing of text data.
- Utilize basic analytics to identify deviations from expected behavior or utilize existing analysis outcomes. Provide suitable textual explanations for the detected anomalies like unusually high battery cell temperature, low pack voltage, normal contactor temperature, etc.
- Employ a diverse range of methodologies (such as few-shot classification, RAGs, Chain-Of-Thoughts) within the realm of LLMs to comprehend the relationship between observations and the content of the knowledge database.
- Rank the most probable failure modes and their associated probabilities under specific observed circumstances.
- Categorize similar observed scenarios linked to different failure modes in the knowledge repository.
- Develop a validation strategy incorporating relevant metrics from literature and assess the results of the analysis.
YOUR PROFILE:
- Bachelor's degree in fields like Applied Statistics/Mathematics, Computer Science, Data Science, Automotive, or Electrical Engineering.
- Practical experience in data analysis, machine learning, natural language processing, and database handling.
- Familiarity or exposure to open-source LLMs, public APIs, and open-source libraries (e.g., Hugging Face) for LLM applications.
- Proficient in Python and the implementation of data analysis techniques and algorithms.
- Capable of working autonomously, conducting experiments, and scrutinizing complex datasets.
- Strong problem-solving skills and critical-thinking aptitude.
- Effective communication capabilities for presenting findings and suggestions.
- Physical presence in Graz is mandatory.
WE OFFER:
- Opportunity for independent thesis preparation with guidance and support from seasoned professionals.
- Engage in knowledge exchange with company experts and leverage their proficiency.
- Immerse yourself in AVL's realm and apply your academic knowledge in a practical setting.
Successful completion of the thesis entitles you to a one-time taxable remuneration.
Do not settle for an ordinary thesis; explore the future of mobility with us. Perhaps you will soon become an integral part of it.
AVL promotes and embraces diversity: Recognizing that diverse perspectives are essential to realize our vision of a more sustainable, secure, and advanced mobility landscape. Varied backgrounds, mindsets, interests, and experiences are pivotal to our success. As an Equal Opportunity Employer, we evaluate all competent applicants irrespective of ethnicity, religion, gender, sexual orientation, or disability status.
