Project description
Our client is a global leader in orthodontic solutions, providing innovative and high-quality products and technologies to orthodontists and patients worldwide. We are looking for an AI Scientist to develop predictive models for orthodontic treatment planning, appliance design, treatment optimization and clinical outcome prediction. The role sits at the intersection of AI, statistical modeling, biomechanics and healthcare data science.
Responsibilities
- Develop predictive and prescriptive ML models for orthodontic appliances and treatment modalities
- Design algorithms that forecast treatment outcomes, duration, tooth movement, patient compliance and appliance effectiveness
- Compare statistical, ML, deep learning, probabilistic and hybrid physics-informed approaches
- Build explainable AI solutions and model validation/monitoring frameworks
- Lead experimental design and statistical analysis; assess bias, uncertainty and clinical significance
- Work with large clinical, imaging, treatment and manufacturing datasets (3D scans, imaging, treatment plans)
- Collaborate with orthodontists, biomechanical engineers, software engineers and product managers
- Contribute to internal publications and IP generation
SKILLS
Must have
- Ph.D. or M.S. in AI, ML, Statistics, Computer Science, Applied Mathematics, Biomedical Engineering or a related quantitative discipline
- 3+ years developing advanced predictive models (industry or research)
- Statistical modeling, ML, predictive analytics, experimental design, hypothesis testing
- Bayesian methods and/or probabilistic modeling
- Python, SQL, scientific computing, ML libraries (PyTorch, TensorFlow, Scikit-learn)
- Ability to learn unfamiliar domains quickly
- Strong communication; explaining complex concepts to non-technical audiences
Nice to have
• Healthcare, medical devices, digital dentistry, orthodontics, biomechanics or regulated environments • Imaging, computer vision, geometric modeling or 3D data • Causal inference and real-world evidence analysis • Explainable AI for healthcare • Publications, patents, research contributions • Cloud ML and MLOps • Leading cross-functional scientific initiatives