Principal Computer Vision Scientist in London

On behalf of a global organisation, I am seeking a Principal Computer Vision Scientist to lead the development of foundation models for biological imaging, with the ambition of accelerating target and biomarker discovery in early drug research.

This role is pivotal in establishing a deeply integrated, multimodal AI framework, using cellular imaging as a core modality alongside molecular data, transcriptomics, and biomedical literature. You will play a pivotal role in shaping how generative AI is applied across Research & Early Discovery, helping to shorten the path from target identification to clinical impact; an exciting opportunity to be at the forefront of integrating AI and machine learning with biological data to drive scientific discovery.

Key Responsibilities:

• Lead the design, development, and deployment of next-generation AI/ML models for cellular imaging and multimodal biological data.
• Define and drive the strategy for integrating generative AI into early-stage drug discovery, working closely with cross-functional research teams.
• Advance state-of-the-art methods in computer vision, deep learning, representation learning, and multimodal foundation models.
• Communicate scientific results through internal reports, executive presentations, and peer-reviewed publications.
• Build and nurture collaborations with academic and industry partners.

Skills/Experience required:

• PhD in Computer Science, Bioinformatics, Computational Biology, Physics, or a related field.
• Hands-on experience pretraining or fine-tuning foundation models for computer vision.
• A strong publication record at leading conferences such as CVPR, NeurIPS, ICLR, or ICML.
• Proven expertise in multimodal representation learning, ideally applied to biological or pharmaceutical data.
• Advanced Python skills and deep experience with PyTorch, Hugging Face, PyTorch Lightning, or similar frameworks.
• Proficiency in modern software engineering practices, including Git, CI/testing, and contemporary Python tooling (e.g. uv).
• The ability to lead independent research while thriving in a highly collaborative, multidisciplinary environment.
• Excellent written and verbal communication skills.
• Experience in one or more of the following would be an advantageous:

• High-content screening, high-throughput perturbative experiments, single-cell RNA-seq, or related data modalities.
• Large-scale model training and deployment using cloud platforms (AWS, Azure, Nvidia DGX Cloud).
• Systems modeling, biophysics, or causal inference in computational biology.
• Writing well-tested, well-documented ML code, following best practices for maintainable research software.

Please apply online with your CV.