Job Description

Within The University of Texas MD Anderson Cancer Center lies a powerful engine driving the future of new targeted, immune- and cell-based therapies: the Therapeutics Discovery Division. Therapeutics Discovery eliminates the bottlenecks that hamper traditional drug discovery, with a multidisciplinary team of dedicated researchers, doctors, drug developers and scientific experts working together to develop small-molecule drugs, biologics and cellular therapies. Our unique structure and collaborative approach allow the team to work with agility, bringing novel medicines from concept to clinic quickly and efficiently - all under the same roof.

The Therapeutics Discovery Division is built around four platforms: The Institute for Applied Cancer Science (IACS), ORBIT (Oncology Research for Biologics and Immunotherapy Translation), TRACTION (Translational Research to Advance Therapeutics and Innovation in Oncology) and the Neurodegeneration Consortium.

The IACS platform is focused on discovering and developing the next generation of small-molecule targeted therapies, driven by the needs we see in our patients. The team aligns world-class drug discovery and development research with the science and clinical care for which MD Anderson is known. We work in a fast-paced, milestone-driven environment with a focus on team science and interdisciplinary research. Our unique approach has created a biotech-like engine within the walls of the nation's leading cancer center to bring life-saving medicines to our patients more quickly and effectively. This model already has achieved results, with multiple programs currently in clinical and late-stage preclinical development.

The Institute Research Investigator, Computational Chemistry in the structural chemistry group of the Institute for Applied Cancer Science (IACS) participates in cross-functional research to advance our drug discovery projects from early exploratory efforts through lead optimization, ultimately delivering therapeutic agents of benefit to patients. As part of the IACS team, the Institute Research Investigator will apply physics-based and machine learning approaches to small molecule design, use structure-based methods to inform compound optimization across small molecule modalities, and leverage modern computational techniques for hit-finding.

By joining the Therapeutics Discovery Division, you have the opportunity to use your talents to make a direct impact on the lives of our patients. We are seeking a highly motivated and collaborative individual to become a part of our team. Ideal candidates will be familiar with the drug discovery process, have experience working with modern commercial and open-source molecular modeling software platforms, and have used in silico techniques to guide the design of novel small molecule therapeutics.

Key Functions

* Apply and develop cutting edge physics-based and machine learning methodologies to enable advancement of Institute projects through leadership and experimental activities. Analyze physicochemical and assay data generated by various studies and leverage results for the data-driven design of future studies.
* Work in close collaboration with medicinal chemists and other project team members in the design and optimization of small molecules with improved potency, selectivity, functional activity, and ADME properties across multiple modalities.
* Evaluate protein targets for "druggability" using structure-guided techniques.
* Carry out virtual screens to identify novel chemical starting points for medicinal chemistry optimization.
* Develop docking models for primary and off-targets to help rationalize SAR and use free-energy methods to help prioritize new analogs for synthesis.
* Analyze compound screening data to identify high-quality leads and develop structure-based hypotheses for their optimization.
* Use QM and MM methods to evaluate small molecule conformations, electrostatics, and reactivity.
* Proactively identify, evaluate, and internalize promising commercial and open-source computational chemistry tools to support drug discovery efforts across TDD.
* Communicate data analysis results to a broad scientific audience from multiple disciplines.
* Employ safe lab practices and maintain research records/laboratory notes.

EDUCATION:
Required: Bachelor's degree in biology, biochemistry, molecular biology, cell biology, enzymology, pharmacology, chemistry or related field.
Preferred: Master's or PhD in chemistry, physics, computer science, biology, biochemistry, bioinformatics, cheminformatics, or related field.

EXPERIENCE:
Required: Six years experience of relevant research experience in laboratory With Master's degree, four years of required experience. With a PhD in a natural science or Medical degree, no experience required.

Preferred: Experience in a pharma or biotech company, or a strong publication record demonstrating the application of computational chemistry to problems of pharmaceutical interest. Scripting proficiency (eg. Python) and programming competency in a low-level language (eg. C/C++, Java). Familiarity with machine learning and AI as applied to drug discovery. Prior experience with protein therapeutics modeling, protein degradation (ternary complex modeling, molecular glues and PROTACs), covalent inhibitor optimization, or AI-based structure prediction would be an asset. Excellent communication, writing, and organizational skills.

Experience with the following:
* Commercial molecular modeling software (eg. MOE, Schrodinger, BioSolveIT, OpenEye)
* Molecular dynamics simulation packages (eg. AMBER, GROMACS, Desmond)
* Chemistry-aware data visualization and analysis tools (eg. StarDrop, SpotFire, Vortex)
* Scientific workflow tools (eg. Pipeline Pilot, KNIME)

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.

Job Tags

Full time, Local area,

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