HHMI is investing in AI to accelerate scientific discovery. The CombinAItorial Sensor Design project aims to develop a protein biosensor optimization pipeline that integrates high-throughput screening with deep learning to visualize dynamic biochemical processes in living cells.
Requirements
- Strong programming skills in Python, PyTorch, and JAX are required.
- Familiarity with protein modeling or machine learning frameworks such as AlphaFold, ESM, Chai-1, or Boltz-1 is highly valued.
- Experience in ML model deployment, workflow orchestration, and high-throughput data processing.
- Experience working with large biological datasets in GPU-based computing environments.
- Familiarity with protein modeling deep learning frameworks (e.g., AlphaFold, ESM, Chai-1, Boltz-1).
- Familiarity with computer vision deep learning frameworks (e.g., SAM, cellpose)
- 3+ years of experience in developing and fine-tuning deep learning models.
Responsibilities
- Develop and maintain computational infrastructure and predictive tools for AI biosensor optimization, including tool development for modeling fluorescence properties and biochemical performance from sequence and structure
- Collaborate with data scientists and experimentalists to develop robust data flows from optical pooled screening outputs through to model training and deployment.
- Implement cutting-edge tools for predicting fluorescence properties and biochemical performance based on protein sequence and structure.
- Collaborate with our microscopy, sequencing, and protein engineering team to ensure the seamless integration of computational and experimental workflows.
- Apply machine learning, AI techniques, and software engineering best practices to deliver scalable, maintainable, and reproducible AI systems for protein engineering
- Carefully document data, code, and processing pipelines to enable seamless reproduction and extension of research results
- Actively contribute to the latest advancements in the field and continuously improve your skillset with the latest advances in AI research and technologies.
Other
- Please include a cover letter with your application detailing your qualifications and experience as they relate to this position.
- Please include a description of one related deep learning model or framework (e.g., AlphaFold, ESM, Chai-1, Boltz-1, etc.) that you have used. Briefly describe what you used it for and tell us about limitations and challenges you encountered.
- Collaborate with interdisciplinary teams, potentially mentor junior engineers, and direct or assist in directing the work of others to meet project goals while advising stakeholders on data strategies and best practices.
- Excellent technical documentation and communication skills, with the ability to convey complex data concepts to both technical and non-technical audiences.
- A detail-oriented, creative, and organized team player with a collaborative mindset.
