AI/ML Research Scientist, Inverse Problems & Machine Learning
About The Position
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. The Chan Zuckerberg Institute for Advanced Biological Imaging (CZ Imaging Institute) is building the next generation of imaging technologies to transform our understanding of biology in health and disease. Over the next decade, we aim to create breakthrough systems - spanning hardware, software, probes, and computational tools - that will empower scientists worldwide. As part of the Chan Zuckerberg Initiative's Imaging Program, the CZ Imaging Institute (https://czii.org/) combines engineering, computation, and biology to tackle grand challenges in biological imaging. Our work is shared broadly with the global scientific community through open science, direct collaborations, and partnerships. The CZ Imaging Institute will create breakthrough technologies - hardware, software, biological probes, data, and platforms - that will be made available to the scientific community and adopted worldwide through a combination of direct access to the institute, open sharing of advances, and commercial partnerships. Researchers will collaboratively develop breakthrough biological imaging systems centered around grand challenges that push the boundaries of what we can see and measure. We are seeking a creative and motivated Data Scientist to develop and apply cutting-edge computational methods for complex imaging problems. This role is ideal for candidates with expertise in applied mathematics, computational science, or physics, combined with modern machine learning approaches. You will design algorithms, build scalable tools, and collaborate across disciplines to advance scientific discovery. This position is on-site in Redwood City, CA.
Requirements
- M.S. or Ph.D. in Applied Mathematics, Computer Science, Physics, Engineering, or a related field.
- 1 - 5 years of relevant experience.
- 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.
- Strong analytical, problem-solving, and communication skills.
- Experience with imaging data (e.g., cryo-EM, tomography, or related modalities).
Nice To Haves
- Familiarity with convex optimization, variational methods, or numerical PDEs.
- Knowledge of GPU computing and high-performance environments.
- Track record of scientific publications or open-source contributions.
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.
Benefits
- Provides a generous employer match on employee 401(k) contributions to support planning for the future.
- Paid time off to volunteer at an organization of your choice.
- Funding for select family-forming benefits.
- Relocation support for employees who need assistance moving
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
Industry
Publishing Industries
Education Level
Ph.D. or professional degree
Number of Employees
11-50 employees
