Postdoctoral Researcher in Foundational AI Models for Molecular Materials

The Department of Chemistry is seeking a Postdoctoral Associate to join our cutting-edge research team at the University of Florida, led by Professors Adrian Roitberg, Professor Richard Hennig, and Professor Mingjie Liu, in a transformative project aimed at revolutionizing chemistry through foundational AI models. The Postdoc Research is expected to develop a novel molecular-graph diffusion model that addresses the challenges of chemical space complexity, data heterogeneity, and the computational demands of data generation across a broad spectrum of materials and properties. The successful candidate will train a molecular-graph diffusion model on an extensive dataset of known molecular structures and fine-tune this model for specific applications using context-driven multimodal learning techniques.

UF is the state’s oldest, largest, and most comprehensive land grant university with an enrollment of over 50,000 students and was ranked 6th in the country among public universities (US News and World Report 2023 rankings), and 1st among public institutions in the Wall Street Journal 2023 survey. UF is located in Gainesville, a city of approximately 150,000 residents in North-Central Florida, 50 miles from the Gulf of Mexico, and 67 miles from the Atlantic Ocean, and within a 2-hour drive to large metropolitan areas (Orlando, Tampa, Jacksonville). The beautiful climate and extensive nearby parks and recreational areas afford year-round outdoor activities, including hiking, biking, and nature photography. UF’s large college sports programs, museums, and performing arts center support a range of activities and cultural events for residents to enjoy. Alachua County schools are highly rated and offer a variety of programs including magnet schools and an international baccalaureate program. Learn more about what Gainesville has to offer at Visit Gainesville.

The salary is competitive and commensurate with qualifications and experience, and the compensation includes a full benefits package. To see more, visit, benefits.hr.ufl.edu.

PhD in Chemistry, Materials Science, Computer Science, or a related field with a strong computational component.

Experience with deep learning and machine learning models, particularly in the context of chemical or molecular applications.

Proficiency in programming languages such as Python, and familiarity with AI frameworks (e.g., TensorFlow, PyTorch).

Demonstrated ability to handle large datasets and perform complex computational analyses.

Excellent communication skills and the ability to work collaboratively in a dynamic research environment.

For full consideration, applications must be submitted online. Click on Apply Now at the top of this posting. 

Please attach:

1. Your CV
2. A cover letter detailing your relevant experience and career objectives
3. The names and email addresses of three references.  An email will be sent to your references, requesting them to upload their confidential letter to the submission packet

Applications will be continuously reviewed until filled.  For questions, please contact Professor Mingjie Liu (mliu@chem.ufl.edu)

All candidates for employment are subject to a pre-employment screening which includes a review of criminal records, reference checks, and verification of education. 

The selected candidate will be required to provide an official transcript to the hiring department upon hire. A transcript will not be considered “official” if a designation of “Issued to Student” is visible. Degrees earned from an educational institution outside of the United States require evaluation by a professional credentialing service provider approved by the National Association of Credential Evaluation Services (NACES), which can be found at http://www.naces.org/. 

The Department of Chemistry is committed to promoting an environment that welcomes all abilities, classes, ethnicities/races, gender identities and expressions. We particularly welcome applicants who can contribute to such an environment through their scholarship, teaching, mentoring, and professional service.