At Huawei Zurich Research Center, we are at the forefront of cutting-edge AI research and development, specializing in creating innovative solutions that push the boundaries of computer vision and deep learning. Our team is a diverse group of passionate researchers, engineers, and creatives dedicated to advancing the state of the art in AI. We are looking for a highly motivated and talented Computer Vision Research Scientist to join our team and lead our efforts in image and video style transfer.

Key Responsibilities:

• Conduct cutting-edge research in computer vision with a focus on image and video style generation and transfer.
• Develop and implement deep learning models and algorithms for real-time style generation and transfer applications.
• Collaborate with cross-functional teams to integrate research outputs into products and services.
• Publish research findings in top-tier conferences and journals.
• Stay up-to-date with the latest advancements in computer vision, deep learning, and related fields.
• Mentor and collaborate with other researchers, engineers, and interns.

Qualifications:

• Ph.D. in Computer Science, Electrical Engineering, or a related field, with a focus on computer vision, deep learning, image/video processing, or a similar area.
• Strong publication record in top-tier computer vision and AI conferences/journals (e.g., CVPR, ICCV, ECCV, NeurIPS, etc.).
• Expertise in deep learning frameworks such as TensorFlow, PyTorch, or similar.
• Extensive experience with image and video processing, neural style transfer, convolutional neural networks (CNNs), generative models, and/or big foundation models.
• Proficiency in programming languages such as Python, C++, or similar.
• Strong problem-solving skills and ability to work independently as well as in a team environment.
• Excellent communication skills and the ability to present complex technical concepts clearly.

Preferred Qualifications:

• Experience with real-time processing and optimization of deep learning models for deployment.
• Familiarity with transfer learning, multi-task learning, and other advanced machine learning techniques.
• Prior experience in leading research projects or teams.
• Strong understanding of the theoretical foundations of deep learning and computer vision.