Our client is a startup in biomedical research in the application of artificial intelligence and machine learning to accelerate biomedical discovery and the development of precision medicine.

ROLE

Your primary focus will be on designing and implementing sophisticated AI models to analyze complex biological and environmental datasets. By leveraging your expertise in machine learning, you will uncover new insights that drive the development of innovative therapies and healthcare solutions

RESPONSIBILITIES

AI Model Development: Design, build, and implement advanced AI models, including deep learning algorithms, tailored to analyze complex biomedical datasets related to molecular biology and environmental factors.

Data Integration: Collaborate with interdisciplinary R&D teams to gather, preprocess, and integrate diverse biomedical datasets, ensuring data quality and relevance.

Analysis and Interpretation: Conduct in-depth AI analyses of biomedical data to uncover critical insights that contribute to the development of new treatments, therapies, or biomedical products.

Predictive Modeling: Develop predictive models to assess risks and opportunities in biomedical projects, supporting decision-making processes in R&D.

Interdisciplinary Collaboration: Work closely with scientists, biologists, engineers, and IT professionals to align AI initiatives with organizational goals and ensure effective model implementation.

Trust Building: Engage with stakeholders to communicate the benefits and limitations of AI in biomedical research, fostering trust and transparency in the technology.

Continuous Improvement: Stay up-to-date on the latest advancements in AI, biomedical modeling, and environmental factors, applying new methodologies to refine models and improve their accuracy.

Documentation and Reporting: Prepare comprehensive documentation of methodologies, findings, and model performance, presenting results to both technical and non-technical audiences.

Team Contribution: Actively participate in team meetings and collaborative projects, sharing insights with other machine learning researchers to drive innovation and improvement

REQUIREMENTS

PhD with 10+ years of experience (including PhD) in at least one of the following areas: Machine/Deep Learning, Computational Biology, Computer Science, Applied Mathematics, or other related quantitative fields.