PhD Researcher in Deep Learning for Data Auditing
vor 3 Wochen
We are seeking a highly motivated PhD researcher to join our team at Robert Bosch GmbH, focusing on deep learning methods for improving and auditing data at scale.
The successful candidate will contribute to the development of novel and automated data auditing methods, leveraging foundation models to enable data analysis at scale, provide insights into models' generalization capabilities, and aid performance estimation in new domains.
Key responsibilities include:
- Developing and implementing deep learning methods for data auditing and quality control
- Collaborating with Machine Learning and Computer Vision experts to advance data filtering and annotation strategies
- Publishing research findings in top-tier journals and conferences
- Discussing and developing new ideas within the Deep Learning research team at Bosch Corporate Research
Requirements:
- Excellent degree in Computer Science or related field with focus on Machine Learning/Deep Learning
- Strong background and experience in Deep Learning, strong programming skills, in particular Python, knowledge in Deep Learning frameworks (TensorFlow, PyTorch, etc.)
- Knowledge and experience in foundation models, generative models, and out-of-distribution detection are a plus
- Motivation to work in an interdisciplinary and international team
- Fluent in English (written and spoken)
We offer a dynamic and inclusive work environment, opportunities for professional growth, and a competitive salary package. If you are passionate about deep learning and data science, we encourage you to apply.
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