Head of Frontier AI Models

We are seeking a highly skilled and innovative Data Scientist to lead the implementation of frontier domain-specific oncology foundation models and to spearhead the development of a transformative agentic framework. This position requires an experienced professional with a robust track record in computational pathology, multimodal data integration, and deep learning.

Key Responsibilities:

• Lead the implementation of oncology-specific frontier foundation models utilizingstate-of-the-art multimodal learning techniques.

• Develop an advanced analytical frameworks and fit-for-purpose agents to optimize clinical oncology workflows and therapeutic decision-making.

• Collaborate closely with interdisciplinary teams including pathologists, genomic scientists, oncologists, and AI researchers to ensure model accuracy and clinical relevance.

• Manage end-to-end development processes from data preprocessing and model training to deployment and interpretability analyses.

• Publish high-impact research findings and contribute actively to scientific discourse within the oncology and AI communities.

Minimum Qualifications:

• Ph.D. in Computer Science or a closely related field with a minimum of 4 years post-graduate experience in AI and computational pathology.

• Extensive experience with deep learning methodologies, particularly self-supervised and multimodal learning, transformers, and convolutional neural networks.

• Past experience and documented track record in leading the development of a frontier foundation model in pathology, OMICs,and/or molecular data.

• Demonstrated success in integrating histopathology imaging, spatial proteomics, and genomic data for predictive analytics.

• Proven experience in developing scalable and reproducible machine learning pipelines using PyTorch or TensorFlow.

• A strong publication record, including contributions to leading journals.

• Proficiency in high-performance computing environments and managing large-scale datasets.

• Exceptional cross-disciplinary communication and collaboration skills.

Desired Qualifications:

• Previous leadership in pioneering research projects integrating histology and genomics data.

• Experience developing machine learning models for cell phenotyping and multiplex spatial proteomics.

• Familiarity with clinical oncology and an understanding of biomarker-driven patient selection strategies.

Why Join Us?

This role offers an exceptional opportunity to shape the future of oncology research and clinical practice through groundbreaking AI-driven innovations. You will collaborate with top-tier interdisciplinary experts, contributing directly to meaningful advancements in patient care and precision medicine.