Nucs AI
Machine Learning Scientist
Salary not disclosedRemote
- Engineering
- Remote
- 3d ago
Newly posted
About the role
Nucs AI is seeking a Machine Learning Scientist to advance research capabilities in clinical oncology. This role focuses on developing novel approaches to medical image analysis, treatment outcome prediction, and multi-modal clinical data integration. The successful candidate will collaborate with physicians and engineers to ensure research is both scientifically rigorous and clinically meaningful.
Responsibilities
- Develop novel ML/DL methods for medical image analysis, including segmentation, lesion detection, and treatment response prediction.
- Design and conduct experiments to evaluate new approaches against clinical baselines and state-of-the-art methods.
- Publish research findings in top-tier venues and represent the company at scientific conferences.
- Collaborate with clinicians and medical physicists to ensure methods are grounded in clinical reality.
- Produce validated research outputs with documented performance benchmarks for production engineering.
- Contribute to clinical validation studies and evidence generation for regulatory submissions.
- Collaborate with external academic research partners on joint studies.
Required skills
- Machine Learning
- Computer Vision
- Medical Image Analysis
- Deep Learning
- CNNs
- Transformers
- U-Nets
- Python
- PyTorch
- Medical Imaging
- Statistical foundations
- Experimental design
- Hypothesis testing
- Survival analysis
- Biostatistics
Nice to have
- Nuclear medicine imaging
- Dosimetry
- PSMA-PET
- FDG-PET
- SPECT
- Multi-modal data integration
- Clinical trial design
- Generative AI
- Graph neural networks
Qualifications
- PhD in machine learning, computer vision, medical image analysis, biomedical engineering, or related field
Benefits
- Equity
- Remote-first
- Flexible working
About the Company
Nucs AI is an early-stage, venture-backed company revolutionizing cancer care through AI and medical imaging technology. Founded in 2024, the team develops AI-powered tools at the intersection of medical imaging, radioligand therapy, and artificial intelligence to improve diagnostic precision and patient outcomes.