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• robustness to distribution shifts, domain adaptation, and domain generalization
• out-of-distribution detection and modeling
• uncertainty estimation
• innovative data curation approaches
• learning under label noise and weak supervision
• synthetic data generation
• fairness research

• Own the end-to-end development of the MOBROG mobile app, from front-end implementation to backend architecture
• Build and maintain cross-platform mobile applications using Flutter

• You will actively work on sparsifying, pruning and quantizing CNN and transformer-based architectures for autonomous driving
• Design, implement, and evaluate models and training algorithms for runtime optimized 3D semantic occupancy predictions

• Hands-on experience building foundations for realtime simulation systems
• The chance to learn, implement and extend state-of-the-art simulation methods (XPBD, advanced constraint solvers, hybrid models)
• Mentorship from PhD-level researchers

You design end-to-end AI and data architectures from data ingestion to model serving, using and extending platforms within our vehicles with a strong focus on edge computing....

End-to-End Data Lifecycle Ownership: Lead the design and implementation of tracking strategies that cover the entire lifecycle: from initial requirements gathering to Generation, and finally to automated Validation....

Strategy and Leadership: Define, communicate, and execute the overall Data Science roadmap and vision for the Generative AI function, ensuring alignment with N26's product and business goals....

Lead and collaborate with cross-functional teams to generate digital biomarker signatures from complex datasets using AI/machine learning, enabling target engagement assessment, patient stratification, and early signals of biological activity....

Marketing Process Architect: You are responsible for the end-to-end automation of our marketing processes. Your goal is to minimize manual operational effort in performance marketing through intelligent workflows....

• Drive pioneering technical advances to the field of foundation models on structured data, as well as exploring world models for solving business problems.
• Expand the horizon of what is possible by bringing together rich semantic context with large scale business data