Associate Scientist (Flow Cytometry, Department of Computational Biology)

The Department of Computational Biology is seeking a motivated and innovative Associate Scientist in Flow Cytometry. This researcher will work closely with the Computational Biology Genomics Laboratory and the iTARGETS team to provide advanced technologies to develop novel immunotherapy for pediatric cancers and assess immune responses to cancer immunotherapy. Key instruments include BD FACSMelody and Bigfoot cell sorter. This role is essential to Computational Biology department efforts in immuno-oncology research and single-cell technology development and involves oversight of flow cytometry instrumentation, assay development, training, and facility operations. The ideal candidate will have hands-on experience with high-parameter cytometry and a commitment to supporting translational immuno-oncology research.

Primary Responsibilities:

Flow Cytometry Instrument Maintenance, Standardization, and Quality Assurance

• Establish, modify, and implement Standard Operating Procedures (SOPs) for routine maintenance and performance evaluation of flow cytometers and associated instrumentation.
• Independently perform instrument setup, sample acquisition, calibration, alignment, and troubleshooting.
• Oversee instrument repair and service coordination.
• Maintain detailed documentation of instrument performance, service logs, and corrective actions to ensure optimal operation and data reliability.

Flow Cytometry Training and User Support

• Train technicians, students, and investigators on cytometry concepts, including instrument startup/shutdown, routine maintenance, sample acquisition, and basic data analysis.
• Educate users on sample preparation requirements tailored to their specific research goals and experimental designs.
• Support users in developing technically sound and biologically relevant cytometry-based approaches.

Experimental Design, Method Development, and Assay Optimization

• Collaborate with the CBGL, iTARGETS team, and Computational Biology PIs to develop, evaluate, and optimize multicolor flow cytometry assays, including high-parameter panels.
• Work independently or collaboratively to design and validate novel analytical methods with attention to accuracy, reproducibility, and biological relevance.
• Present new techniques and applications to the broader research team and adapt innovations into routine workflows.

Core Facility Operations and Resource Management

• Manage laboratory resources, including supply ordering and inventory control.
• Oversee compliance with institutional safety policies related to chemical, biological, and instrument operations.
• Support budgeting, cost-recovery tracking, fee development, and reporting metrics.
• Supervise and mentor technical staff, setting goals, delegating tasks, and providing developmental feedback.

Technology Assessment, Data Analysis, and Continuing Education

• Stay abreast of emerging cytometry platforms, analytical software, reagents, and immunological techniques.
• Evaluate and implement new tools for flow data analysis and reduction; train users on software solutions as needed.
• Develop and refine data analysis strategies in collaboration with the CBGL, iTARGETS team and investigators.
• Engage in continuing education and present innovative methodologies in single-cell and spatial omics to enhance the department’s impact on cutting-edge translational research.

Experience: 

Proficient knowledge of immunology. Demonstrated success in training others. Demonstrated experience with data analysis platforms and making figures suitable for scientific presentations (e.g., FlowJo, DiVa, Omiq), Microsoft Office products (e.g., Word, Excel, PowerPoint), and other common tools. Training in bacteriological, viral, chemical, and physical safety. Proficiency with Macintosh or PCs and handheld devices. Able to work safely in a BSL2 environment.

Professional Growth Opportunities:

The Department of Computational Biology offers a collaborative environment with access to various cutting-edge omics technologies, high-performance computing, cloud computing, innovative visualization tools, and automated analytical pipelines. Researchers interact with leading cancer and translational researchers, contributing to high-impact projects and participating in national and international meetings. The department supports innovative research with its infrastructure, including a wet-lab component, providing flexibility to develop individual research programs.

Location:

This position is based in Memphis, TN (100% on-site) with relocation assistance available.

Minimum Education and/or Training:

• Bachelor’s degree in a relevant scientific area is required

Minimum Experience:

• 5+ years of research experience is required

• 3+ years of experience is required with a Master’s degree

• No prior experience required with a PHD

• Strong knowledge and experience in understanding and application of underlying principles related to techniques being performed

• Experience in R&D methods and processes in lab setting, and execution of research projects for the laboratory preferred

• Proven performance in earlier role/comparable role

Compensation

In recognition of certain U.S. state and municipal pay transparency laws, St. Jude is including a reasonable estimate of the compensation range for this role. This is an estimate offered in good faith and a specific salary offer takes into account factors that are considered in making compensation decisions including but not limited to skill sets, experience and training, licensure and certifications, and other business and organizational needs. It is not typical for an individual to be hired at or near the top of the salary range and compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current salary range is $65,520 - $114,400 per year for the role of Associate Scientist (Flow Cytometry, Department of Computational Biology).

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