PhD - Foundation Models for Improving and Auditing Data at Scale
Aufgaben
We 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).
Profil - 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)
- 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)
Kontakt & Wissenswertes
https://www.bosch-ai.com
www.bosch.com/research
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)
+49(9352)18-8527
Need further information about the job?
Dan Zhang (Functional Department)
+49(711)811-23687
Einblicke in unsere Arbeitswelt
Willkommen in Renningen
Unser Forschungscampus in Renningen bildet den internationalen Knotenpunkt unserer Bereiche Forschung und Vorausentwicklung, Cross-Domain Computing Solutions und Bosch Center for Artificial Intelligence. Mitarbeiter aus aller Welt arbeiten daran, Antworten auf die Fragen von Übermorgen zu finden. Damit sich die Ideen unserer Forscher optimal entfalten können, ist der Campus ein Netz der kurzen Wege zwischen Kommunikation und Inspiration, an dem der Kreativität keine Grenzen gesetzt sind. Wollen auch Sie die Zukunft gestalten? Wir freuen uns auf Ihre Neugier und Innovationsfreude.
