AI Cheminformatics Scientist for Drug Discovery (Hybrid)

University of Texas MD Anderson Cancer Center; Houston (TX); Hybrid; USD 107,000 - 160,000; Full time

Job summary

University of Texas MD Anderson Cancer Center is seeking an AI-driven Computational Chemist to advance the A3D3a platform for adaptive, AI-augmented drug discovery. The role focuses on generative models, large data, and QSAR/QSPR modeling to identify novel cancer therapeutics.

Collaboration with senior scientists and cross-disciplinary teams is essential. Ideal candidates hold an MSc and have experience with Python, PyTorch, RDKit, and cheminformatics tools, including PyMol and VMD.

Qualifications

• Requires MSc in Chemistry, Biochemistry, Computer Science, or related field.
• Experience with large data and willingness to learn new approaches are critical.
• Three years of scientific software or industry development/analysis experience; with MSc, one year; with PhD, no experience required.

Responsibilities

• Apply generative models to propose chemical matter for targets of interest.
• Develop novel methods in coordination with senior scientists.
• Develop QSAR/QSPR models from public and internal data.
• Document work thoroughly.
• Produce output for scientific publications and contribute to said publications.
• Present results at multidisciplinary project meetings and external meetings.
• Attend collaborator meetings; manage multiple projects efficiently.

Skills

Python

Unix

Cheminformatics

AI/ML for chem/cheminformatics

Molecular generation

PyTorch

rdkit

GPU computing

Education

MSc in Chemistry/Biochemistry/CS or related field

PhD in related field preferred

Bachelor's degree in related field

Tools

PyMol

VMD

ChEMBL

Job description

University of Texas MD Anderson Cancer Center is seeking an AI-driven Computational Chemist to advance the A3D3a platform for adaptive, AI-augmented drug discovery. The role focuses on generative models, large data, and QSAR/QSPR modeling to identify novel cancer therapeutics.

Collaboration with senior scientists and cross-disciplinary teams is essential. Ideal candidates hold an MSc and have experience with Python, PyTorch, RDKit, and cheminformatics tools, including PyMol and VMD.