Description:
As an AI Scientist at BIOS Life, you will drive the research and development of the machine-learning systems powering our personalized cancer surveillance platform. Your work will span foundation models, cancer risk prediction, biomarker detection, longitudinal monitoring, and reinforcement-learning systems designed to recommend optimal screening and follow-up strategies.
You will help keep BIOS Life at the forefront of AI, healthcare, and biology, shape our research roadmap, and translate scientific advances into practical clinical applications.
Reporting to the Head of AI, you will work closely with our clinical, product, and engineering teams. As an early-stage hire, you will have significant influence over our scientific direction, technical approach, and research culture.
Key Responsibilities
Research Strategy & Scientific Innovation
- Survey the AI, genomics, and oncology literature to identify emerging methods and high-impact research opportunities.
- Help shape the research roadmap and advance the state of the art in AI-driven cancer surveillance.
- Translate scientific questions and clinical needs into actionable research priorities.
Machine Learning Model Development
- Design, train, and evaluate models for cancer biomarker detection, risk stratification, and longitudinal monitoring.
- Develop and investigate reinforcement-learning approaches to recommend personalized screening and survivorship strategies.
- Fine-tune and adapt foundation models to genomic, electronic health record (EHR), and other relevant biomedical data.
Research-to-Production
- Partner with engineering to translate research prototypes into scalable, reliable production systems.
- Bridge multimodal learning and clinical workflows, ensuring research outputs can support real-world applications.
- Contribute to the development of modern AI pipelines and infrastructure.
Scientific Evaluation & Rigor
- Design rigorous experimental frameworks and benchmarking strategies to evaluate model performance.
- Develop and contribute to clinical validation protocols, with appropriate attention to generalizability, robustness, and limitations.
- Maintain high standards of scientific integrity, reproducibility, and technical quality.
Publications & Scientific Communication
- Lead and contribute to peer-reviewed publications, conference papers, and technical reports.
- Communicate complex technical findings clearly to scientific, clinical, and cross-functional audiences.
- Represent BIOS Life in scientific forums and collaborations with academic and clinical partners.
Cross-Functional Collaboration
- Work closely with oncologists, epidemiologists, product managers, and engineers to align research with clinical needs and product objectives.
- Collaborate across disciplines to turn promising scientific advances into meaningful improvements in cancer surveillance.
What You Bring
Required Qualifications
- PhD in Machine Learning, Computer Science, Computational Biology, Bioinformatics, or a related quantitative field.
- Strong publication record in applied AI, including large-scale machine learning or foundation models, and/or research at the intersection of AI, biology, and healthcare.
- Hands-on experience training and evaluating machine-learning models.
- Proficiency in Python and modern ML frameworks such as PyTorch, JAX, or TensorFlow.
- Familiarity with cloud-based GPU/TPU computing and modern machine-learning pipelines.
- Solid software engineering fundamentals, including version control, testing, and code review.
- Excellent scientific writing and communication skills, with the ability to explain complex concepts to technical and clinical audiences.