Data Scientist Cheminformatics and Computational

University of Texas MD Anderson Cancer Center

Houston (TX)

Hybrid

USD 107,000 - 160,000

Full time

12 days ago

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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

At UT MD Anderson we seek a talented, energetic, and collaborative AI-driven Computational Chemist to conduct both routine and novel analyses as part of our flagship platform A3D3a: Adaptive, AI-augmented, Drug Discovery and Development. With experience in molecular generation, foundation models, and QSAR/QSPR modeling, the AI Computational Chemist will contribute to the discovery of novel cancer therapeutics as part of A3D3a.

Led by Prof. Bissan Al-Lazikani, Director of Therapeutics Data Science, the intelligent and ever-learning A3D3a platform is part of MD Anderson's Therapeutics Data Science initiative and part of our ambitious Institute for Data Science in Oncology. A3D3a will accelerate the discovery and impact of novel therapies for cancer by enabling novel opportunities for optimized therapies for patients with a focus on rare and hard-to-treat cancers through the development of novel machine learning and AI technologies.

Central to this vision, the AI Computational Chemist will leverage state-of-the-art generative and foundation models and, collaboratively with senior scientists, develop innovative data science approaches to propose chemical matter, propose drug-target interactions of on- and off-target effects, and rationalize toxicity patterns. While physics- or docking-based approaches may complement work in this position, proficiency in AI/ML based computational chemistry and cheminformatics is a must.

The ideal candidate should have at least a MSc in Chemistry, Biochemistry, Computer Science, or a related field. Expertise and comfortability with large data and a willingness to learn new approaches is critical to this role.

Why Us? At UT MD Anderson, this role offers the opportunity to help advance innovative cancer research through the development of cutting-edge artificial intelligence and machine learning technologies.

Employer-paid medical coverage starting day one for employees working 30+ hours/week, plus optional group dental, vision, life, AD&D, and disability insurance.

Accruals for PTO and Extended Illness Bank, plus paid holidays, wellness, childcare, and other leave options.

Tuition Assistance Program after six months of service and access to extensive wellness, fitness, and employee resource groups.

Defined-benefit pension through the Teachers Retirement System, voluntary retirement plans, and employer-paid life and reduced salary protection programs.

Job 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 as well as external meetings

Other Duties

Attend collaborator meetings and team working group meetings. Prioritize and manage multiple projects in a timely and resource-effective manner.
Stay up to date with relevant literature, gather information systematically, and confer with the supervisor regarding new procedures.

Ideal candidate will have Cheminformatics and Computational experience with an advanced degree for 2+ years plus:

Expertise in scientific computing using Python in a Unix environment, comprising of GPU computing
Proficient with generative AI for molecular generation
Proficient in PyTorch, rdkit, and other machine/deep learning utilities for cheminformatics
Familiar programmatically accessing public databases such as ChEMBL
Experience with molecular visualization tools (i.e., PyMol, VMD)
Familiar with basic statistical testing

Education

Required: Bachelor's Degree Biomedical Engineering, Electrical Engineering, Computer Engineering, Physics, Applied Mathematics, Science, Engineering, Computer Science, Statistics, Computational Biology, or related field.

Preferred: Master's Degree Science, Engineering or related field. PhD Science, Engineering or related field.

Experience

Required: Three years scientific software or industry development/analysis experience. With Master's degree, one year experience. With PhD, no experience required.

Preferred: Computational Chemist

The University of Texas MD Anderson Cancer Center offers excellent benefits, including medical, dental, paid time off, retirement, tuition benefits, educational opportunities, and individual and team recognition.

This position may be responsible for maintaining the security and integrity of critical infrastructure, as defined in Section 113.001(2) of the Texas Business and Commerce Code and therefore may require routine reviews and screening. The ability to satisfy and maintain all requirements necessary to ensure the continued security and integrity of such infrastructure is a condition of hire and continued employment.

It is the policy of The University of Texas MD Anderson Cancer Center to provide equal employment opportunity without regard to race, color, religion, age, national origin, sex, gender, sexual orientation, gender identity/expression, disability, protected veteran status, genetic information, or any other basis protected by institutional policy or by federal, state, or local laws unless such distinction is required by law.

Additional Information