Scientist I Machine Learning for Generative Shape Modeling

$89,100 - $110,200/Yr

Allen Institute - Seattle, WA

Full-time - Entry Level

Remote - Seattle, WA

Ambulatory Health Care Services

About the position

The Scientist I position at the Allen Institute for Cell Science focuses on developing machine learning workflows for generative shape modeling from single cell image data. This role is integral to the Computational Cell Science team, which aims to create scalable, quantitative image-based analysis frameworks to understand cellular behavior. The position emphasizes collaboration, diversity, and the application of machine learning in biological contexts.

Responsibilities

• Develop and implement scalable and reproducible machine learning pipelines for 3D shape quantification on data from microscopy image-based assays.
• Systematically, efficiently and reproducibly iterate on new models.
• Maintain and improve existing machine learning pipelines.
• Work closely with other teams in the institute to scale-up analysis protocols into a high throughput computational pipeline.
• Ensure seamless integration and sharing of resources and data across teams.
• Maintain rigorous quality control standards.
• Maintain meticulous records and work closely with other scientists to coordinate complex experiments.
• Adhere to SOPs, GLPs and regulatory requirements.
• Prepare written summaries and present activities internally and publicly.

Requirements

• Ph.D. in Computational Physics, Applied Physics, Applied Mathematics, Computer Science, Biological Science, or related field; OR equivalent combination of degree and experience.
• Extensive knowledge in machine learning and hands-on experience in developing and implementing deep learning algorithms and generative models like VAEs, GANs, autoregressive models and transformers.
• Experience with image-based biology assays; some experimental and/or microscopy image analysis experience would be an advantage.
• Experience with different data representations like images, point clouds, meshes; some computational geometry experience would be an advantage.
• Experience with developing or contributing to open-source tools/packages.
• Experience utilizing software engineering practices such as version management, build management and testing.

Nice-to-haves

• Experience with MLOps tools like MLflow, prefect would be an advantage.
• Careful attention to detail.
• Excellent interpersonal skills.
• Experience working in a multi-disciplinary environment in academic or industrial settings.
• Ability to work both independently and in a collaborative, multi-disciplinary environment.

Benefits

• 401(k)
• Dental insurance
• Health insurance
• Life insurance
• Paid time off
• Vision insurance