PhD - Foundation Models for Improving and Auditing Data at Scale
vor 2 Wochen
Robert-Bosch-Campus 1, 71272 Renningen, Germany
Full-time
Robert Bosch GmbH
Company DescriptionAt Bosch, we shape the future by inventing high-quality technologies and services that spark enthusiasm and enrich people's lives. Our promise to our associates is rock-solid: We grow together, we enjoy our work, and we inspire each other. Welcome to Bosch.
The Robert Bosch GmbH is looking forward to your application
Job DescriptionWe conduct cutting-edge deep learning research with a focus on data. We are looking for a motivated PhD student eager to delve into research on deep learning methods for improving and auditing data, as well as to explore their real-world applications for further improving the performance, reliability, and efficiency of AI models.
The goal of this position is to develop novel and automated data auditing methods, leveraging foundation models. These methods shall enable data analysis at scale, provide insights into models' generalization capabilities and aid performance estimation in new domains. Additionally, outcomes from data auditing will be utilized to improve data quality, e.g., pruning less relevant samples, adding more valuable ones, and generating advanced annotations to expedite learning with smaller models and model evaluation.
- As a PhD student in our team, you will innovate and automate data auditing methodologies for analyzing data diversity, coverage as well as biases, leveraging deep generative models and foundation models.
- In addition, you will advance data filtering and annotation strategies to optimize training efficiency as well as streamline model evaluation processes.
- You collaborate with Machine Learning as well as Computer Vision experts and publish in top-tier journals as well as conferences.
- Furthermore, you will discuss and develop new ideas within the Deep Learning research team at Bosch Corporate Research (CR).
- Education: excellent degree in Computer Science or related field with focus on Machine Learning/Deep Learning
- Experience and Knowledge: 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 as well as out-of-distribution detection are a plus
- Enthusiasm: motivation to work in an interdisciplinary and international team
- Languages: fluent in English (written and spoken)
The final PhD topic is subject to your university.
Start: July 2024
Diversity and inclusion are not just trends for us but are firmly anchored in our corporate culture. Therefore, we welcome all applications, regardless of gender, age, disability, religion, ethnic origin or sexual identity.
Need support during your application?
Sarah Schneck (Human Resources)
Need further information about the job?
Dan Zhang (Functional Department)
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