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.
Preferred Skills and Experience
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.
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
Benefits
Health insuranceVision insurance
Additional Information
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.
Learn more about the CoE-SCB and our research vision at:
https://www.stjude.org/research/centers-of-excellence/center-of-excellence-for-structural-cell-biology.html
Environment
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.
The World's Brightest Minds Always Innovate
At St. Jude Children's Research Hospital, we know what can be achieved when the brightest scientific minds face the fewest barriers. That's why we provide world-class facilities, state-of-the-art technologies, extraordinary support, and a collaborative bench-to-bedside environment where you can see firsthand how your work translates into discoveries that impact children's lives. At St. Jude, we encourage you to dream big and stop at nothing when it comes to advancing science and improving human health.
Stjude · Memphis, TN