Deep Learning Researcher

About the job

Join a technology company focused on developing advanced AI and computer vision solutions

is a biotechnology company that is transforming the practice of histopathology using AI-powered virtual staining

What You'll Be Doing

• Design and implement novel computer vision and deep learning algorithms
• Conduct experiments to evaluate algorithm performance and validate research hypotheses
• Keep up to date with state-of-the-art research in the field
• Conduct research in machine learning, deep learning, and statistical modeling to develop novel AI algorithms.
• Design, prototype, and implement ML models for real-world applications.
• Work with large datasets to train, validate, and optimize ML models.
• Publish findings in top-tier conferences and journals, contributing to the broader ML research community.
• Collaborate with software engineers, data scientists, and domain experts to integrate research into production systems.
• Optimize models for efficiency, accuracy, and scalability in deployment environments.
• Develop tools and frameworks to streamline ML research and experimentation.
• Develop and enforce best practices for data engineering, data governance, data quality, and security across on-premises and cloud-based data platforms.

Requirements

• MSc, PhD (preferred) in Electrical Engineering, Computer Science, or a related field
• Expertise in computer vision and deep learning, with specific focus on:

Vision Transformers

Diffusion Models

Image Representation in Latent Space

Generative Adversarial Networks (GANs)

Semantic segmentation

Classical Image enhancement and image denoising

• Proficiency in Python, MATLAB, etc., and ML frameworks such as PyTorch
• Strong mathematical foundation in linear algebra, probability, and optimization
• Cloud expertise, with hands-on experience in AWS, GCP, or Azure, including data warehousing and distributed computing solutions
• Experience with large-scale model training, distributed computing, or cloud ML infrastructure

Job No. 416046

CV to [email protected]