Senior Data Scientist – Computer Vision & Biomedical Imaging Full-time

Senior Data Scientist – Computer Vision & Biomedical Imaging

Our Artificial Intelligence Machine Learning (AI/ML) capabilities are critical accelerators to our mission to delivering towards inventing new medicines that save and improve lives. Core to the Data, AI, and Genome Sciences (DAGS) function is an AI/ML-first approach to improving target and biomarker discovery, validation and selection and elucidating complex disease mechanisms. As Senior Data Scientist for Foundation Model you will be responsible for developing, training, and implementing advanced AI/ML methodologies and techniques to identify disease biology from large scale biological data. You will be part of a cross-functional team of computational biologists, bioinformaticians, data scientists, software engineers, and machine learning engineers that strive to identify therapeutic targets. Experience with modern computer vision architectures (e.g., CLAM, Swin Transformers, Segment Anything) is highly valued.

What You'll Do:

• Design and develop, train, and implement novel ML algorithms particularly transformer-based Foundation Models for Target discovery leveraging large scale biological and imaging data.
• Rapidly prototype and iterate on model architectures using real-world data
• Integrate multi-modal data (e.g., histology, spatial omics) into scalable learning frameworks
• Collaborate with biologists and data scientists to define modeling goals and interpret results
• Contribute to our long-term AI/ML strategy for drug discovery
• Publish research findings in relevant conferences and journals and actively contribute to the scientific community through knowledge sharing and collaborations.

You Should Have:

• PhD in Computer Science, Engineering, Data Science, AI/ML, Bioinformatics, Computational Biology, Genetics & Genomics, Mathematics, Statistics, Physics, Pharmaceutical Science, or related STEM field with 0+ years postdoctoral experience or Master's degree with 4+ years of industry experience.
• Strong background in deep learning, digital pathology, computer vision, and/or medical image analysis
• Experience with large-scale model development and training (e.g., CNNs, transformers, contrastive/self-supervised learning)
• Strong expertise and experience in modern AI/ML approaches, transformer-based Foundation models, representation learning, and related methodologies.
• Proficiency in programming languages such as Python, and experience with deep learning frameworks and libraries like PyTorch, etc.
• Interest in life sciences problems and disease biology, and willing to learn from and teach others.
• Excellent communication skills and ability to work collaboratively in multi-disciplinary team.

Preferred Skills and Experience:

• Familiarity with life science data is a plus.
• Relevant publications in scientific journals and experience contributing to research communities, including NeurIPS, ICML, ICLR, etc.
• Exposure to spatial transcriptomics or multi-modal biomedical data