Data Scientist for Deep Learning Model Optimization

vor 2 Wochen


Aachen, Nordrhein-Westfalen, Deutschland Fraunhofer-Gesellschaft Vollzeit
Job Description

We are seeking a highly motivated and skilled researcher to work on a Bachelor/Master thesis project at the Fraunhofer Institute for Production Technology IPT in Aachen. The project focuses on optimizing deep learning models for production use cases by generating synthetic data.

Project Overview

The application of deep learning models to automate visual process monitoring and quality control enables quality and efficiency gains in production. However, the lack of representative training data, such as data of quality-critical anomalies, is a significant challenge. To address this issue, we aim to design effective augmentation pipelines that enrich existing datasets with synthetic images. The successful candidate will investigate how optimization methods, such as Bayesian optimization, can be used to optimize augmentation pipelines for individual use cases in production.

Responsibilities
  • Conduct literature research on deep learning, image augmentation, and global optimization methods
  • Identify requirements for designing efficient augmentation pipelines in production use cases
  • Develop and implement a method for optimizing augmentation pipelines
  • Experimentally validate the approach based on a practical use case in the field of computer vision
  • Prepare and document the results
Requirements
  • Studying mechanical engineering, industrial engineering, computer science, or a comparable subject
  • First experience in Python programming
  • Basic knowledge of machine/deep learning theory and methods
  • Self-responsible and structured way of working
  • Good language skills in German and/or English
What We Offer
  • Scientific work on a current and practice-relevant topic
  • Professional supervision and support for your thesis
  • Participation in innovative research and industry projects with industry partners
  • State-of-the-art machine park equipped with edge cloud systems and 5G infrastructure

We value and promote the diversity of our employees' skills and therefore welcome all applications - regardless of age, gender, nationality, ethnic and social origin, religion, ideology, disability, sexual orientation, and identity. Severely disabled persons are given preference in the event of equal suitability.



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