Scientific Assistant in Real-Time Generative Models and Computer Models 100%

ETH Zurich; Zürich; On-site; CHF 90,000 - 130,000; Full time

Benefits offered by this job

Public transport season tickets

Car sharing

ASVZ sports program

Childcare support

Pension benefits

Job summary

ETH Zurich's Biomedical Image Computing Group seeks a candidate to implement and optimize real-time deep-learning image-enhancement models for endoscopic videos. The role focuses on translating architectures into efficient pipelines, profiling for low latency, and integrating camera data with preprocessing steps in collaboration with an industrial partner.

The position is immediately available for up to 8 months, based in Zürich, Switzerland, with emphasis on practical deployment and

Qualifications

• MSc in CS, ML, medical image computing, or a related field.
• Experience with neural-network image processing pipelines.
• Excellent Python programming skills.
• Experience with PyTorch.

Responsibilities

• Implement, optimize, and deploy deep-learning image-enhancement models for real-time operation.
• Translate architectures into efficient real-time processing pipelines connected to an industrial camera system.
• Profile and optimize models for low-latency inference and integrate camera acquisition and preprocessing pipelines.
• Contribute to project deliverables and scientific manuscript preparation.

Skills

Python

PyTorch

Real-time processing

Profiling tools

CUDA/C++

Education

MSc degree in computer science, machine learning, medical image computing, or a related field

Tools

TensorRT

ONNX

CUDA

Job description

The Biomedical Image Computing Group develops algorithmic solutions to enable automatic interpretation and forming of biomedical images, aiming to increase efficiency and accuracy in clinical practice and research.

Project background

The enhancement of endoscopic videos is a critical yet complex task. These videos are integral to various clinical interventions, where the clarity of imaging data is essential for procedural success. Due to challenging imaging conditions, the quality of endoscopic videos can be significantly compromised by a range of artifacts. This project seeks to develop the next generation of enhancement algorithms tailored for endoscopic videos, with a focus on applications in real-time interventions. Development efforts will prioritize both enhancement quality and computational efficiency, particularly with respect to latency.

The successful candidate will join the BMIC team at ETH Zurich and also be part of the Computer Vision Lab (CVL). The project is conducted in collaboration with an industrial implementation partner, who will provide support with hardware and software integration. The position is open immediately and initially limited to 8 months.

Job description

This position involves the implementation, optimization, and deployment of deep-learning image-enhancement models for real-time operation. Rather than focusing primarily on model training, the successful candidate will work on translating existing and new architectures into efficient real-time processing pipelines connected directly to an industrial camera system. Typical tasks will include profiling and optimizing models for low-latency inference, implementing and adapting neural-network architectures with real-time constraints in mind, integrating camera acquisition and preprocessing pipelines, and contributing to project deliverables and scientific manuscript preparation.

Profile

• 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.
• Experience implementing and validating neural-network architectures using PyTorch.
• Demonstrable experience with model deployment/acceleration (PyTorch, ONNX, TensorRT, CUDA/C++, etc.), profiling tools, and camera/sensor integration is a plus.

We offer

• Your job with impact: Become part of ETH Zurich, which not only supports your professional development, but also actively contributes to positive change in society
• You can expect numerous benefits, such as public transport season tickets and car sharing, a wide range of sports offered by the ASVZ, childcare and attractive pension benefits

Working, teaching and research at ETH Zurich

We value diversity and sustainability

In line with our values, ETH Zurich encourages an inclusive culture. We promote equality of opportunity, value diversity and nurture a working and learning environment in which the rights and dignity of all our staff and students are respected. Visit our Equal Opportunities and Diversity website to find out how we ensure a fair and open environment that allows everyone to grow and flourish. Sustainability is a core value for us - we are consistently working towards a climate-neutral future.

Curious? So are we.

Further information about Biomedical Image Computing can be found on our Website.