Post Doc Associate

Posting Summary In this position, the post doctorial associate will use robotics driven by machine learning / artificial intelligence to explore the self-assembly of polymers and their interactions with proteins. The Gormley Lab has been developing these data driven tools to explore highly complex problems in macromolecular chemistry. It is our strong belief that machine learning, when complemented with an automated workflow, provides an ideal platform for designing advanced nanomaterials that are perhaps too complex to rationally design. This project is highly cross‑disciplinary and requires expertise in data science, machine learning, and programming in Python. Additional experience in polymer synthesis/characterization, macromolecular characterization, enzymes, and basic assays are ideal. Candidates who are computational only will be considered if they see themselves applying machine learning tools to physical problems in macromolecular chemistry. Due to the multidisciplinary nature of the project, the candidate will be expected to collaborate heavily with others in the Gormley Lab as well as other labs at Rutgers and Princeton University. We are hoping to hire two post doctorial associates for a set of projects. The listed projects are fully supported by NIH and NSF grants. Preferred Qualifications Familiarity with nanomaterials (synthesis, functionalization, and characterization) and enzymes. Strong publication track record and ability to work well in teams. #J-18808-Ljbffr Rutgers University