Senior Computational Scientist / Scientific Software Engineer for Cryo-ET Workflow Development
About The Position
The St. Jude Center of Excellence for Structural Cell Biology (CoE-SCB) is seeking an innovative and highly motivated Senior Computational Scientist / Scientific Software Engineer to develop next-generation computational infrastructure for cryo-electron tomography (cryo-ET), and structural cell biology workflows. This position sits at the interface of structural biology, high-performance computing (HPC), machine learning, and scientific software engineering. The successful candidate will work closely with experimental scientists, computational researchers, and HPC engineers to design scalable, automated, and reproducible pipelines that support cryo-ET workflows ranging from data collection and preprocessing to segmentation, subtomogram averaging, and large-scale data analysis. The role offers the opportunity to help shape the future computational ecosystem of the CoE-SCB and contribute to transformative imaging workflows spanning molecular to cellular structural biology. The Center of Excellence for Structural Cell Biology (CoE-SCB) at St. Jude is building advanced multimodal and multiscale imaging workflows integrating cryoEM, cryo-ET, cryo-volume EM, cryo-FIB milling, machine learning, and large-scale computational analysis. The successful candidate will work within a highly collaborative environment alongside world-class scientists, computational engineers, and technology developers to create next-generation platforms for structural cell biology.
Requirements
- Advanced proficiency in Python, Linux, and shell scripting.
- Strong software engineering and system design experience across local, HPC, and cloud computing environments.
- Experience developing scientific software pipelines and automation frameworks.
- Expertise in handling and processing large scientific datasets, including efficient storage, retrieval, and distributed processing strategies.
- Experience with SQL databases and Object-Relational Mapping (ORM) frameworks.
- Bachelor's degree and 7+ years of relevant experience.
- Master's degree and 5+ years of relevant experience.
- PhD with 2+ years of relevant experience.
- Prior experience in computational research techniques and processes.
- Proven performance in earlier role/comparable role.
Nice To Haves
- Familiarity with Cryo-EM/Cryo-ET software ecosystems such as RELION, CryoSPARC, Warp, AreTomo, Dynamo, PyTom, EMAN2, SerialEM, Tomography 5, or related tools.
- Experience with workflow orchestration, containerization, or distributed computing technologies is highly desirable.
- Experience developing user interfaces and web-based tools using modern web technologies (HTML, CSS, JavaScript) is beneficial.
- Familiarity with machine learning and AI-based image analysis approaches is desirable.
- Strong commitment to reproducible research, maintainable codebases, and collaborative software development practices.
- Excellent communication and collaboration skills in multidisciplinary scientific environments.
- Master's degree or PhD preferred.
- 1-2 first author papers IF > 10 (or equivalent contribution to other research outputs).
Responsibilities
- Design, develop, and maintain scalable computational pipelines for cryo-ET workflows with a high level of automation and reproducibility.
- Architect software solutions optimized for local workstations, HPC systems, and cloud-based environments.
- Refactor existing analysis workflows into modular, maintainable, and reusable software components and libraries.
- Develop user-friendly APIs and interfaces for data analysis, workflow management, and visualization.
- Work closely with CoE-SCB scientists, faculty, and HPC engineers to identify computational bottlenecks and implement scalable, high-performance solutions for cryo-ET workflows.
- Develop and optimize workflows for large-scale cryo-ET datasets, including preprocessing, tomographic reconstruction, segmentation, template matching, subtomogram averaging, and AI/ML-assisted analysis.
- Evaluate, benchmark, and integrate emerging computational tools and technologies into existing workflows.
- Implement robust software engineering practices, including version control, testing, profiling, optimization, logging, and error handling.
- Scale local analysis workflows to distributed HPC and cloud infrastructures while ensuring efficient data handling and storage integration.
- Assist with software deployment, troubleshooting, and standardization across the CoE-SCB computational ecosystem.
- Maintain clear and comprehensive code documentation and user documentation.
- Participate in cross-disciplinary projects involving machine learning, image analysis, visualization, and large-scale structural biology datasets.
- Contribute to the strategic development of computational infrastructure supporting multimodal and multiscale structural cell biology workflows.
- Lead computationally focused scientific research projects with minimal supervision from their PI.
- Develop new computational methods.
- Identify, process, organize, interpret, review, and report relevant data.
- Direct data collection.
- Present research to colleagues within and outside the institution; draft a complex manuscript with minimal supervision, as required.
- Regularly train and oversee the work of others in computational research and procedures.
- Perform other duties as assigned to meet the goals and objectives of the department and institution.
- Maintains regular and predictable attendance.
Benefits
- world-class facilities
- state-of-the-art technologies
- extraordinary support
- collaborative bench-to-bedside environment
- exceptional benefits
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What This Job Offers
Job Type
Full-time
Career Level
Senior
