Postdoctoral Research Associate - AI-driven Lab Automation for Life Sciences

Brookhaven National Laboratory • Ridge, NY

5d • $71,900 - $119,000 • Onsite

About The Position

Brookhaven National Laboratory’s National Synchrotron Light Source II (NSLS-II) seeks a Postdoctoral Research Associate for AI-driven Lab Automation for Life Sciences for an on-site position in the Biological, Environmental and Planetary Science Division. The aim of the position is to advance the frontiers of structural biology by developing AI-driven methods for improving crystal quality at scale. This role will enable new discoveries in life sciences and bio-technology relying on structural biology methods. The ideal candidate would have a background and an interest in Biophysics, Biochemistry, Artificial Intelligence and Machine Learning. Join a team of scientists at the leading macromolecular crystallography beamlines, the crystallization laboratory, the computing center and contribute to science projects at the interface between AI method development and large-scale research facilities.

Requirements

• Ph.D. 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.
• Experience working with Python, scientific software development, version control and collaborative code development, such as Git
• Ability to work in interdisciplinary teams.
• Strong publication record.

Nice To Haves

• Experience with machine learning frameworks (PyTorch, TensorFlow, etc.) and integrating ML in a research lab facility.
• Familiarity with lab automation or robotics.
• Experience with black-box optimization, including active learning or Bayesian optimization.
• Experience with imaging, time-series or high-dimensional data.
• Exposure to crystallography or structural biology.
• Experience with multimodal datasets and developing reproducible workflows.
• Familiarity with experiment tracking and metadata capture.

Responsibilities

• Develop and implement AI-enabled laboratory-workflows for automated crystallization screening, optimization, and characterization integrating imaging, experimental metadata, and diffraction outcomes.
• Design and deploy computer vision methods to detect and track crystal growth.
• Develop closed-loop optimization approaches to recommend crystallization conditions and harvesting strategies based on experimental feedback.
• Develop, train and integrate AI/ML models with laboratory automation systems, including crystallization robotics, liquid handlers, and imaging platforms.
• Build scalable data pipelines linking experimental metadata, imaging data, and diffraction results for high-throughput analysis.
• Evaluate model performance using experimental metrics and support deployment into user-facing workflows.
• Collaborate with synchrotron beamline scientists and laboratory and crystallization staff.
• Document methods and results, contribute to manuscripts and reports, and present the work at conferences.
• Participate in interdisciplinary team science.

Benefits

• Comprehensive employee benefits program

What This Job Offers

• Job Type: Full-time
• Career Level: Entry Level
• Education Level: Ph.D. or professional degree