Postdoctoral Associate in AI-Driven Drug Discovery – Yanjun Li Lab

Laplace Expert Ltd; Gainesville, Northern (FL, KY); Hybrid; USD 52,000 - 68,000; Full time

Job summary

University of Florida in Gainesville seeks a postdoctoral researcher in AI-driven drug discovery and computational chemistry. The role focuses on deep-learning approaches for small-molecule design and molecular-interaction modeling, with opportunities to publish and present findings.

The postdoc will work at the interface of medicinal chemistry, data science and AI, and engage with collaborators across disciplines.

Qualifications

• Recent PhD or equivalent in computer science, computational chemistry, electrical/computer engineering, data science, informatics, biomedical engineering or a related field.

Responsibilities

• Apply AI and computational chemistry to discovery and optimization of small molecules targeting RNA or proteins.
• Develop or use deep-learning approaches for molecular generation and optimization.
• Model molecular interactions and analyze computational datasets.
• Collaborate with multidisciplinary drug-discovery collaborators.
• Publish, present and contribute to grant activity.

Skills

Deep learning

Molecular design

Molecular optimization

Computational chemistry

Molecular interaction modeling

Data science

Education

Recent PhD (CS, computational chemistry, ECE, data science, informatics, bioengineering)

Job description

University of Florida · Department of Medicinal Chemistry

Florida, United States

About This Opportunity

The Yanjun Li Lab at the University of Florida seeks a postdoctoral researcher in AI-driven drug discovery and computational chemistry, including deep-learning approaches for small-molecule design and molecular-interaction modeling.

This postdoc applies artificial intelligence and computational chemistry to the discovery and optimization of small molecules targeting RNA or proteins. The researcher will develop or use deep-learning approaches for molecular generation and optimization, model molecular interactions, analyse computational datasets and work with multidisciplinary drug-discovery collaborators. The appointment also includes publication, presentation and contribution to grant activity. The project is positioned at the interface of medicinal chemistry, data science and AI, making it suitable for candidates from computer science, computational chemistry, engineering, informatics or biomedical engineering.

AI drug discovery computational chemistry deep learning small molecules RNA targets protein targets

Level Postdoc

Time Commitment Full-time

Reference Code 539075

Field AI-Driven Drug Discovery

Specialization Artificial Intelligence & Data Science

Organization Type University

Funding & Compensation

• Amount Paid
• Funding Type Salary
• Funding Status Paid

Requirements

Education

Recent PhD or equivalent in computer science, computational chemistry, electrical/computer engineering, data science, informatics, biomedical engineering or a related field.

Experience

Technical Skills

• Deep learning
• Molecular design
• Molecular optimization
• Computational chemistry
• Molecular interaction modeling
• Data science

General Skills

• Interdisciplinary collaboration
• Scientific writing
• Research presentation