Transformer Model Architecture Research Software Package
Contact: skross@fredhutch.org
Introduction:
This project involves building a Python and PyTorch-based software package to empower transformer model architecture research for biomedical data scientists. The ideal candidate should have a strong background in Python programming, Python package development and documentation, machine learning, artificial intelligence, and PyTorch.
Objective:
To deliver software, documentation, and a matching conceptual framework for modular, iterative construction of transformer models.
Tasks and Responsibilities:
- Development of Transformer Model Framework
- Design and implement a flexible framework for transformer models using PyTorch, focusing on modularity and iterative construction.
- Ensure the framework is adaptable for various biomedical research applications.
- Collaborate with biomedical data scientists to understand their specific needs and incorporate feedback into the framework design.
- Python Package Development and Documentation
- Develop a Python package that encapsulates the transformer model framework, ensuring ease of installation and use.
- Write comprehensive documentation that covers setup, usage, and troubleshooting, catering to both beginners and advanced users in the biomedical field.
- Ensure the package is ready for routine maintenance and improvement.
- Integration and Validation of Machine Learning Models
- Integrate machine learning models within the transformer framework, focusing on accuracy and efficiency in processing biomedical data.
- Ensure that thorough testing and validation of models is enabled by the framework to ensure reliability and robustness in various biomedical research scenarios.
Required Skills and Qualifications:
- Strong Python Programming Skills: Proficient in Python with experience in developing Python packages and libraries.
- Expertise in PyTorch: In-depth knowledge of PyTorch, especially in building and optimizing transformer models.
- Experience in Machine Learning and AI: Solid understanding of machine learning algorithms and artificial intelligence, particularly in the context of biomedical applications.
- Software Development Best Practices: Competence in software development methodologies, version control (e.g., Git), and software testing and validation.
- Strong Documentation Skills: Ability to create clear, user-friendly documentation for software packages, ensuring accessibility to a range of users from various backgrounds.
- Problem-Solving and Analytical Skills: Excellent problem-solving abilities and analytical thinking, crucial for developing innovative solutions in transformer model research.
- Communication and Collaboration Skills: Strong verbal and written communication skills, essential for collaborating effectively with cross-functional teams and understanding user requirements.
Deliverables:
- Transformer Model Framework: A fully functional and flexible transformer model framework developed in PyTorch.
- Python Package: A comprehensive Python package that encapsulates the transformer model framework, ready for deployment and use.
- Documentation: Detailed documentation for the Python package, including setup instructions, usage guides, examples, and troubleshooting tips.
- Testing Infrastructure: Comprehensive software testing demonstrating the efficacy, reliability, and robustness of the transformer model framework.
Timeline:
The expected completion time for this project is 6 months. Specific deadlines for each deliverable will be discussed and agreed upon once the project commences.