A postdoctoral research associate position is available with Dr. Christoph Gorgulla.

This project aims to advance computational drug discovery by developing and applying innovative deep learning-based methods to identify novel small-molecule therapeutics. Tackling this challenge is critical for enabling more precise and efficient discovery efforts against complex biological targets that currently lack effective treatments, such as Parkinsons Disease. By combining machine learning with quantum chemistry and structure based approaches, the project will accelerate the translation of computational predictions into experimentally validated drug leads.

Position Responsibilities:

• Design and execute computational screening campaigns to identify and prioritize candidate small molecules for experimental validation, with a focus on developing generalizable workflows and tools.

• Develop or refinement methodologies that improve hit identification, pose prediction, or scoring accuracy, and apply them in drug discovery projects.

• Collaborate closely with other scientists within the lab and with external academic or industrial partners to translate computational predictions into testable hypotheses.

• Mentor graduate students or interns in computational techniques, reproducible workflows, and best practices in data-driven discovery.

• Contribute to manuscript preparation, grant proposals, and presentations, with opportunities to co-lead sections related to methods or results.

• Participate in professional development activities, including conference attendance, skill-building workshops, or cross-disciplinary training.

Minimum Education and/or Training:

A Ph.D. in computational chemistry, structural biology, bioinformatics, computer science, pharmaceutical sciences, or a closely related field. Candidates with significant experience in molecular modeling, virtual screening, quantum chemistry, or machine learning for drug discovery are especially encouraged to apply.

Special Skills, Knowledge, and Abilities:

Required Skills, Knowledge, and Abilities

• Very strong background and skills in deep learning and machine learning

• Machine learning frameworks, in particular PyTorch

• Experience in drug discovery or ability to adapt quickly to applied domains such as drug discovery

• Proficiency in programming or scripting (e.g., Python, Bash, or similar) for workflow automation and data analysis.

• Ability to think critically about experimental data and translate findings into actionable research directions.

• Excellent communication skills, both written and verbal, with the ability to present findings clearly to collaborators from diverse scientific backgrounds.

• Self-motivated, organized, able to contribute to a team-oriented environment.

Preferred Skills

• Computational molecular modeling, computational biology, computational drug discovery, cheminformatics, and/or quantum chemistry

• Cuda, TensorFlow

• Familiarity with common tools for structure-based molecular modeling or virtual

• Experience developing or benchmarking computational methods for drug discovery, scoring functions, predictive models or quantum chemistry

• Machine learning or AI frameworks applied to molecular discovery.

• Familiarity with cloud or high-performance computing environments.

• Experience collaborating with experimental scientists or participating in multidisciplinary projects.

• Prior mentorship of students or involvement in team-based problem solving.

• Interest in contributing to manuscripts, grant proposals, or open-source software.

About the lab and St. Jude:

Our lab operates with a mentorship philosophy centered on trust, curiosity, and growth: trainees receive as much guidance and support as needed, while also being encouraged to explore ideas independently and build ownership over their work. We strive for a kind, collaborative, and intellectually generous team culture—one where people challenge bold scientific problems together while celebrating each other’s success. Above all, we are united by a shared drive to tackle high-impact challenges in computational science that have the potential to transform human health.

St. Jude Children’s Research Hospital is a world-class research institution dedicated to pediatric cancer and other catastrophic diseases of childhood. The first and only National Cancer Institute (NCI)-designated Comprehensive Cancer Center devoted solely to children. Our 300 faculty work across the spectrum of basic, translational, clinical, and population science in a highly collaborative multidisciplinary environment that includes a Nobel laureate and members of the National Academy of Science and the National Academy of Medicine. St. Jude is ranked on Fortune Magazine’s “Best Workplaces in Health Care & Biopharma” and Glassdoor’s “Best Places to Work,” and is located in the heart of Memphis, Tennessee, a vibrant and friendly city at the historic American crossroads of music, trade, food and culture.

We are in pursuit of the brightest minds in biomedical sciences, individuals poised to contribute to our research progress. Other than access to top-quality scientists and mentors, as a postdoctoral trainee at St. Jude, you will have:

• A Blend of Academic Freedom and Industrial Efficiency: Access to shared resources and facilities led by expert scientists, coupled with cutting-edge technology, accelerates research productivity.

• Customized Professional and Career Growth: Experience specifically designed programs to enhance professional growth and career readiness empowering postdocs for success beyond their training. This includes access to grant writing workshops, individual development plans, teaching and mentoring opportunities, non-research career advancement programs, professional development allowance, and so much more.

• Competitive Compensation: Embark on your journey with a competitive salary starting at $72,500 a year, comprehensive benefits and generous relocation assistance, reflecting our commitment to recognize and invest in talent.

• A Sense of Community: St. Jude fosters a vibrant postdoc community that supports a well-balanced life. A dynamic environment promotes connections and camaraderie among postdocs from all backgrounds.

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