Machine Learning Scientist

About Nucs AI Nucs AI is revolutionizing cancer care through cutting-edge AI and medical imaging technology. Founded in 2024 by a multidisciplinary team of oncologists, AI researchers, and healthcare innovators, we’re tackling one of medicine’s most pressing challenges: the growing demand for accurate, timely cancer diagnostics in the face of rising scan volumes and limited radiologist capacity. We sit at the intersection of diagnostics and treatment planning—building AI-powered tools at the convergence of medical imaging, radioligand therapy, and artificial intelligence. Starting with prostate cancer and expanding across oncology, we partner with world-leading medical institutions and pharmaceutical companies across the US, Europe, and Australia to bring precision oncology into everyday clinical practice. Our mission is to enhance diagnostic precision and expand access to expert-level cancer care, improving patient outcomes worldwide. We’re venture-backed, early-stage, and building a team that blends deep clinical expertise with engineering intensity—moving with the rigor the medical field demands and the speed the problem deserves. The Opportunity Nucs AI is looking for a Machine Learning Scientist to deepen our ML research capabilities in clinical oncology. This is a senior, research-oriented role for someone who wants to develop novel approaches to medical image analysis, treatment outcome prediction, and multi-modal clinical data integration - and see those methods reach real clinical settings. You’ll work at the intersection of ML research and clinical application, collaborating closely with physicians, medical physicists, and experienced engineers with deep domain expertise. Together, you’ll develop methods that are scientifically rigorous and clinically meaningful. Your work will directly shape our product capabilities and contribute to peer-reviewed science. What You’ll Do Research & Method Development Develop novel ML/DL methods for medical image analysis, including segmentation, lesion detection, longitudinal tracking, treatment response prediction, and outcome modeling Design and conduct experiments to evaluate new approaches against clinical baselines and state-of-the-art methods Stay current with the literature and propose research directions that advance Nucs AI’s product and scientific goals Publish findings in top-tier venues (MICCAI, RSNA, JNM, Medical Image Analysis) and represent Nucs AI at scientific conferences Clinical Translation Collaborate with clinicians and medical physicists to ensure methods are grounded in clinical reality Produce validated research outputs with documented performance benchmarks and clear handoff specifications for production engineering Contribute to clinical validation studies and evidence generation for regulatory submissions External Engagement Collaborate with external academic research partners on joint studies Support scientific diligence with pharma and clinical partners Contribute to Nucs AI's scientific credibility in the field What You Bring PhD in machine learning, computer vision, medical image analysis, biomedical engineering, or related field Strong publication record in relevant venues (medical imaging, clinical ML, computer vision) Experience structuring and executing research collaborations with academic and clinical institutions Deep expertise in deep learning architectures for image analysis (CNNs, transformers, U-Nets, etc.) Strong programming skills in Python and deep learning frameworks (PyTorch preferred) Experience working with medical imaging data (PET/CT, MRI, or similar modalities) Strong statistical foundations - experimental design, hypothesis testing, survival analysis, and clinical biostatistics Bonus Points Experience with nuclear medicine imaging & dosimetry (PSMA-PET, FDG-PET, SPECT) Expertise in treatment outcome prediction, survival analysis, or longitudinal modeling Experience with multi-modal data integration (imaging + clinical + genomic) F