Postdoc: AI-Driven Lab Automation for Life Sciences

Brookhaven Science Associates, LLC; Upton (NY); On-site; USD 71,900 - 119,000; Full time

Job summary

Brookhaven National Laboratory's NSLS-II seeks a Postdoctoral Research Associate to lead AI-driven lab automation for life sciences, focusing on structural biology and crystal growth. This on-site role advances crystal quality at scale and enables new discoveries in life sciences and biotechnology.

The position involves developing AI-enabled workflows for automation, computer-vision for crystallization, closed-loop optimization, and data pipelines; collaboration with beamline scientists; strong

Qualifications

• PhD in computer science, bioinformatics, biophysics, applied mathematics, or related field.
• Expertise in machine learning, computer vision, or image analysis.
• Experience with data management and databases.
• Proficient with Python and scientific software development including Git.

Responsibilities

• Develop AI-enabled lab workflows for automated crystallization screening and characterization.
• Design and deploy computer-vision methods to track crystal growth.
• Create closed-loop optimization for crystallization conditions.
• Integrate AI/ML models with automation systems (robotics, liquid handlers, imaging).
• Build data pipelines linking metadata, imaging data, and diffraction results.
• Evaluate model performance with experimental metrics.
• Collaborate with beamline scientists and crystallization staff.
• Document methods; contribute to manuscripts and conferences.
• Participate in interdisciplinary team science.

Skills

Machine learning

Computer vision

Image analysis

Python programming

Git

Data management

Interdisciplinary teamwork

Scientific software development

Publication record

Education

PhD in a relevant field

Tools

PyTorch

TensorFlow

Lab automation familiarity

Job description

Brookhaven National Laboratory's NSLS-II seeks a Postdoctoral Research Associate to lead AI-driven lab automation for life sciences, focusing on structural biology and crystal growth. This on-site role advances crystal quality at scale and enables new discoveries in life sciences and biotechnology.

The position involves developing AI-enabled workflows for automation, computer-vision for crystallization, closed-loop optimization, and data pipelines; collaboration with beamline scientists; strong