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Promotion - Effiziente Neuronale Repräsentation von Datensätzen

Renningen, BW, de🌐 Remote💼 Full-time🗓 2026-09-11 → 2026-09-26

Core

Researching deep generative models to create data-efficient representations for training and validating downstream neural networks for Bosch systems.

Role type

PhD Researcher (Deep Generative Models)

Builds

Novel learning algorithms for on-demand data synthesis and improved training efficiency using generative models.

Domain

Artificial Intelligence, Deep Learning, Computer Vision

Deliverable

research

Required skills

Deep Learning, Computer Vision, Python programming, Deep Generative Modeling, Foundation Models

Preferred skills

Peer-reviewed publications, experience with Diffusion Models, GANs, VAEs

Technologies

TensorFlow, PyTorch

Responsibilities

Develop new approaches to adapt deep generative models as data sources, utilize controllability of generative base models for dataset management, discuss and develop new ideas with Deep Learning and Computer Vision experts, publish results in high-ranking journals and conferences.

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