Biohub is leading the new era of AI-powered biology to cure or prevent disease through its 501c3 medical research organization, with the support of the Chan Zuckerberg Initiative, by developing breakthrough technologies and advancing scientific discovery
Requirements
- Strong foundation in inverse problems, optimization, or computational modeling
- Experience in machine learning and deep learning (e.g., PyTorch, TensorFlow)
- Proficiency in Python or C++, and familiarity with scientific computing libraries
- Experience with imaging data (e.g., cryo-EM, tomography, or related modalities)
- Familiarity with convex optimization, variational methods, or numerical PDEs
- Knowledge of GPU computing and high-performance environments
Responsibilities
- Develop and apply algorithms for solving inverse problems in imaging and related computational challenges
- Use optimization, applied mathematics, and physics-inspired modeling to extract insights from high-dimensional data
- Incorporate modern machine learning and deep learning techniques to improve reconstruction, denoising, and feature detection
- Build robust, scalable pipelines for large-scale biological datasets
- Collaborate with biologists, microscopists, and engineers to design solutions aligned with scientific goals
- Contribute to technical documentation, publications, and presentations
Other
- M.S. or Ph.D. in Applied Mathematics, Computer Science, Physics, Engineering, or a related field
- 1 - 5 years of relevant experience
- Strong analytical, problem-solving, and communication skills
- Onsite position requiring you to be onsite for approximately 4 days a week
- Relocation support for employees who need assistance moving
