THESIS WORKER -SMART REPORT CLASSIFICATION USING MACHINE LEARNING AND GENERATIVE AI

Thesis Worker at Volvo Cars  Welcome to explore the world of Volvo Cars by writing your thesis with us! As a thesis worker in our organization you are supported by a supervisor who follows you during your project.
All thesis projects are arranged in business critical areas and therefore you will be able to contribute to our company purpose – providing freedom to move in a safe, sustainable and personal way – from day one! About this opportunity - Background In the Product Validation and Function Architecture department, we manage a substantial fleet of cars for Volvo Cars employees.
This fleet is instrumental in our continuous efforts to enhance product quality and performance.
We receive a significant volume of reports from the drivers of this fleet, which are crucial for various operational and quality improvements.
Ensuring these reports reach the appropriate departments in time for further action is essential.
Given the large number of reports, manual processing is inefficient.
To address this, we have implemented a traditional machine learning model to classify these reports.
While this model has been effective, it has limitations in terms of accuracy.
As we continue to collect more data, our goal is to enhance the performance of this model using more advanced machine learning techniques.
Concurrently, advancements in generative AI present an opportunity to further improve the classification process.
Generative AI models have demonstrated exceptional capabilities in understanding and generating human-like text, making them a promising tool for this task.
By investigating both traditional machine learning and generative AI models, we aim to achieve superior classification accuracy and efficiency.
Scope of the thesis work The primary objective of this project is to implement and evaluate a smart report classifier using.
1-    Traditional machine learning models 2-    Generative AI models The scope of the project includes.
•    Data Collection and Preprocessing.
Gathering and preparing the dataset of driver reports for training and evaluation.
•    Review Work.
Reviewing the existing machine learning model and evaluating its performance.
•    Model Development.
Training and implementing various classical machine learning models as well as a generative AI model tailored for this classification task.
•    Performance Evaluation.
Comparing different relevant metrics for the classification task and overall performance of the generative AI model against the classical and existing machine learning models.
•    Deployment and Integration.
Exploring the feasibility of integrating the generative AI model, as well as the classical model with the best performance, into the existing workflow for real-time classification.
This project aims to investigate both traditional machine learning and generative AI to achieve superior classification accuracy and efficiency, ultimately enhancing the operational processes within our department.
What you´ll bring We are looking for candidates who meet the following criteria.
Educational Background.
Enrolled in a Master’s program in Computer Science, Data Science, Artificial Intelligence, or a related field.
Technical Skills.
-    Proficiency in programming languages such as Python.
-    Experience with machine learning frameworks (e.
., TensorFlow, PyTorch, Scikit-learn).
-    Familiarity with generative AI models and natural language processing (NLP) techniques.
-    Familiarity with containerized solution (Docker) -    Familiarity with version control for software development (git) -    Analytical Skills.
Strong problem-solving abilities and experience in data analysis.
-    Communication Skills.
Ability to clearly document and present research findings.
-    Teamwork.
Willingness to collaborate with cross-functional teams and stakeholders.
This project offers a unique opportunity to work on cutting-edge AI technology and contribute to the enhancement of operational processes within our department.
If you are passionate about AI and eager to tackle real-world challenges, we encourage you to apply.
Duration •    The work will start in January/ to be discussed •    The duration for this thesis work is 20 weeks.
•    30 ECTS (academic credits) if in agreement with your Thesis Advisor in University •    This thesis is to be conducted by 2 Students working in pair.
Selection will be ongoing during the application period, so do not hesitate to send in your application.
Attach your CV and personal letter stating your interests within the given area and your thoughts and credentials.
Apply as soon as possible but no later than  Please note that applications via email will not be accepted.
If you have any additional questions regarding the thesis work, you are welcome to contact.
Manager, Martina Steineck at Supervisor, Ehsan Yasari at Volvo Cars - Driving change together Volvo Cars’ success is the result of a collaborative, diverse, and inclusive working environment.
Today, we are one of the most well-known and respected car brands, with around employees across the globe.
At Volvo Cars, your career is designed around your skills and aspirations, allowing you to reach your fullest potential.