Real-Time Endoscopic Video Enhancement Engineer

ETH Zurich; Zürich; On-site; CHF 80,000 - 110,000; Full time

Job summary

ETH Zurich's Biomedical Image Computing Group is developing real-time enhancement algorithms for endoscopic videos used in clinical interventions. The project aims to translate state-of-the-art architectures into low-latency pipelines connected to industrial cameras, balancing enhancement quality with speed.

The successful candidate will join the BMIC group and CVL, collaborating with an industrial partner for hardware/software integration.

Qualifications

• MSc degree in computer science, machine learning, medical image computing, or a related field.
• Familiarity with neural-network-based image processing pipelines.
• Excellent programming skills and experience with Python.

Responsibilities

• Implementation, optimization, and deployment of deep-learning image-enhancement models for real-time operation.
• Profile and optimize models for low-latency inference; adapt architectures for real-time constraints.
• Integrate camera acquisition and preprocessing pipelines; contribute to project deliverables and manuscripts.

Skills

Python programming

PyTorch

C++

Camera integration

Education

MSc degree in computer science / ML / medical image computing

Tools

ONNX

TensorRT

CUDA

Job description

ETH Zurich's Biomedical Image Computing Group is developing real-time enhancement algorithms for endoscopic videos used in clinical interventions. The project aims to translate state-of-the-art architectures into low-latency pipelines connected to industrial cameras, balancing enhancement quality with speed.

The successful candidate will join the BMIC group and CVL, collaborating with an industrial partner for hardware/software integration.