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Job Description
- Spearhead the research and development of advanced machine learning models to process and interpret clinical data. Ensure models are optimized for accuracy and efficacy within the medical domain.
- Oversee the development, training, and testing of AI models, with a specific emphasis on their application in healthcare and medical research.
- Lead and mentor a team of researchers and developers in deploying AI models within a hybrid cloud environment. Ensure best practices in software development and model deployment are followed.
- Manage the software development team to ensure timely and successful delivery of AI-driven products, meeting both technical and business requirements.
- Create comprehensive documentation detailing the implementation, verification, and validation of algorithms and models, ensuring transparency and reproducibility.
- Apply state-of-the-art bioinformatics and statistical tools to analyze large-scale and complex datasets. Develop innovative approaches for the integration and analysis of biological data.
- Partner with internal and external collaborators to enhance and invent new methodologies for large-scale biological data analysis and integration, fostering a collaborative research environment.
Qualifications
- PhD in Bioinformatics, Statistics, Computer Science, or a related field, with substantial expertise in machine learning and software development.
- Proven experience in developing AI models across various domains such as NLP, imaging, and speech. Proficiency in Python and major AI frameworks (e.g., scikit-learn, TensorFlow, PyTorch).
- Familiarity with machine learning platforms and services from cloud providers such as AWS, GCP, and Azure. Knowledge of big data technologies and cloud computing is advantageous.
- Demonstrated ability to write and contribute to research articles and grant proposals. Previous exposure to healthcare data is a plus.
- Exceptional analytical, technical, and problem-solving abilities. Strong capability in interpreting complex datasets and deriving actionable insights.
- Excellent written and verbal communication skills. Proven experience in delivering technical presentations to diverse audiences.
- Experience in leading research teams and managing projects within a research or development setting.
