Staff Scientific Computing Engineer - Quantum Education

As a Staff Scientific Computing Engineer in the Education Unit, you will play a central role in developing, delivering, and maintaining St. Jude's quantum computing educational ecosystem. You will design and implement training programs, onboarding materials, workshops, tutorials, documentation, and interactive learning experiences to help scientists across St. Jude understand and use quantum computing for biomedical and chemical research. You will collaborate closely with quantum researchers, computational scientists, software engineers, and external partners to translate cutting-edge quantum technologies into accessible, impactful educational content.

Key Responsibilities

• Develop and maintain educational materials for quantum computing, including tutorials, lecture content, hands-on exercises, coding examples, and self-paced training modules.
• Provide technical training and onboarding for faculty, postdocs, Sr. Research Scientists, and trainees wanting to integrate quantum computing into their research.
• Create, organize, and deliver workshops, short courses, lectures, seminars, and hackathons for the St. Jude scientific community.
• Work with Hub leadership to identify educational needs and design curricula tailored to biomedical and chemical applications.
• Build documentation, guides, and best-practice materials that support quantum algorithm development, quantum chemistry workflows, and hybrid quantum-classical pipelines.
• Support collaborative research projects by helping teams understand quantum approaches relevant to their domain.
• Assist in developing outreach and community-building programs related to quantum education across St. Jude.
• Evaluate and integrate new quantum hardware and software capabilities into the training ecosystem.
• Help maintain code repositories, example notebooks, and reproducible demonstration workflows for multiple quantum platforms.
• Contribute to grant proposals and project reports related to quantum education, training, and outreach.
• Support the organization of symposia, workshops, summer schools, and visiting-lecturer programs.
• Foster a collaborative, inclusive, and intellectually vibrant training environment within the Quantum Computing Hub.

Minimum Qualifications

• Bachelor's degree with 5+ years of experience in relevant area (e.g., applied mathematics, physics, chemistry, bioinformatics, computer science, data science, computational biology, computer engineering) (OR) Master's degree with 3+ years of relevant experience.
• Significant experience (including code repositories or published works) in independent scientific analyses and/or image data management.
• Demonstrated experience in one or more applied computational fields: application of modern machine learning methodology, algorithms, computational modeling, finite element analysis, computational geometry, fluid mechanics, scientific visualization, HPC and distributed computing.
• Substantial experience in programming (i.e., fluent in two or more common computer languages).
• Demonstrated experience in the analysis and management of scientific data, including one or more of the following: scientific data visualization, scientific computer code optimization, development of machine learning solutions, deep learning, numerical optimization, application of advanced statistical methods, and development of scientific software.
• Experience working with large data volumes.
• Proven performance in earlier role/comparable role.

Preferred Qualifications

• PhD in Physics, Computer Science, Chemistry, Engineering, or a related discipline.
• Demonstrated expertise in quantum computing, quantum algorithms, or quantum machine learning.
• Strong experience with quantum programming frameworks (e.g., Qiskit, CUDA-Q, Pennylane).
• Proficiency in Python and experience developing clean, well-documented code.
• Proficiency with deep learning frameworks such as PyTorch or TensorFlow.
• Experience with quantum chemistry, quantum simulation, or hybrid quantum-classical workflows.
• Excellent teaching, presentation, and communication skills.
• Proven ability to explain complex scientific concepts to diverse audiences.
• Experience designing or teaching courses, tutorials, bootcamps, or computational workshops.
• Experience developing scientific documentation or training material for research platforms.
• Prior involvement in community-building or outreach programs.
• Experience mentoring trainees or providing technical instruction.
• Strong organizational and project management skills.
• Familiarity with biomedical or chemical research applications.
• Experience contributing to grant writing, large collaborative proposals, or curriculum development.
• Ability to work independently and collaboratively in a fast-paced, interdisciplinary environment.