We are seeking a Director of Machine Learning and Applied Research to lead a multidisciplinary team in designing and deploying machine learning solutions that bridge cutting-edge research and real-world clinical application. In this role, you will spearhead efforts in advanced solutions to assist treatment implementation, biomarker discovery, clinical trial optimization, and the advancement of precision medicine through AI-driven innovation.

A major focus of this position is treatment planning in oncology, with strong emphasis on internal and external radiotherapy, as well as adjacent domains such as interventional radiology. You will lead initiatives that apply multimodal AI models to improve treatment personalization, therapeutic response prediction, and clinical workflow efficiency across these high-impact modalities. You will also be responsible for the maintenance, continuous improvement, and regulatory compliance of our existing products and medical devices, ensuring their robustness, safety, and relevance in rapidly evolving clinical environments. This includes overseeing software upgrades, post-market surveillance, and integration of new clinical insights into deployed solutions.

Leading a team of 15+ engineers and scientists, you will transform imaging, molecular, genetic, and clinical data into actionable insights for prognosis, treatment planning, and therapeutic decision-making. You will champion the development of explainable, high-performance ML/AI models that integrate multi-omics, histopathology, imaging, EHRs, and real-world evidence—while upholding scientific rigor, clinical utility, and fairness.

Collaboration is at the heart of this role. You will work closely with internal teams across bioinformatics, clinical operations, regulatory, and product development, as well as with external partners including academic institutions, CROs, and pharmaceutical companies. You will support regulatory submissions for AI-based diagnostics, develop frameworks for continuous model validation and refinement, and contribute to shaping the strategic roadmap of our commercial products.

Required:

• PhD or MD/PhD in Machine Learning, Statistics, Computer Science, Computational Biology, Biomedical Informatics, or related field.

• 15+ years of experience applying ML with “preferred” emphasis on computer vision, biomedical or clinical contexts, especially in oncology or precision medicine.

• Strong publication or patent record in computer vision and/or medical image analysis and/or biomarker discovery and/or AI in healthcare, or adjacent domains.

• Experience leading interdisciplinary teams, ideally across data science, translational research, and clinical development, with track record on scientific leadership and effective execution of roadmaps.

Preferred:

• Experience working with multi-modal datasets: omics (digital pathology, imaging, and/or EHR).

• Familiarity with FDA/EMA regulatory frameworks for diagnostics or AI-based software.

• Previous involvement in developing or validating companion diagnostics or treatment selection tools.