Position Summary:

The Associate Director, Imaging AI & Quantitative Biomarkers will drive the application of computational imaging, machine learning, and quantitative biomarker approaches to support clinical development and translational research in ophthalmology.

The role focuses on retinal imaging data, including OCT, FAF, fundus imaging, and derived biomarkers. The successful candidate will work closely with imaging and clinical datasets, evaluate AI-based and quantitative methods, and translate analytical outputs into clinically meaningful insights.

This role is suited for a technically strong, scientifically curious individual who can move from a clinical or translational question to a robust analytical approach, critically interpret results, and communicate findings clearly across disciplines.

(Please note that this role was originally advertised as Associate Director/Director AI and Innovation.  If you have already applied for the role under the original title, there is no need to apply again.)

Responsibilities: 

Computational Imaging and Data Analysis

• Analyze longitudinal retinal imaging and linked clinical datasets, including OCT, FAF, fundus imaging, and derived biomarkers.
• Develop and implement image analysis workflows for segmentation, registration, feature extraction, quantification, quality control, and assessment of output reliability.
• Apply and evaluate machine learning and computer vision approaches for clinical research applications

Biomarker & Endpoint Development

• Support the development and validation of novel biomarkers for retinal diseases
• Contribute to endpoint development and data-driven evidence generation for clinical development
• Characterize biomarker progression and treatment-response patterns

Project Execution and Scientific Contribution

• Independently structure and deliver analytical workstreams from problem definition to results
• Work closely with clinical, translational, medical, and biometrics colleagues, translating technical findings clearly across disciplines.
• Contribute to presentations, decision documents, publications, and regulatory-supporting materials as appropriate

Qualifications: 

Required

• Advanced degree, such as PhD, MSc, or equivalent experience, in data science, biomedical engineering, computer science, physics, medical imaging, quantitative biology, medicine, or a related field
• Strong hands-on experience with medical image analysis, biomedical data analysis, computer vision, or machine learning
• Proficiency in Python and common scientific computing and ML libraries
• Strong understanding of quantitative methods, model evaluation, statistical robustness, and data quality control
• Clear communication skills and ability to translate technical results into scientific and clinical insights
• Self-driven, pragmatic, and comfortable working in a dynamic biotech environment

Strongly Preferred:

• Experience with ophthalmology, retinal imaging, OCT, FAF, fundus imaging, or inherited retinal diseases.
• Experience with image segmentation, image registration, longitudinal imaging analysis, or quantitative imaging biomarkers.

What We’re Looking For (Beyond the CV): 

We are looking for someone who enjoys working directly with data, images, models, and code.

The ideal candidate can turn an open scientific question into a concrete analysis, is comfortable with messy real-world biomedical datasets, and has a strong bias toward execution. They can judge whether an AI or imaging output is robust, interpretable, and useful for decision-making - not just technically impressive.

This role is highlighted as a London hybrid role.  We will accept applications from within Europe