Staff Scientist (Automation Lead)

RSC comprises four integrated groups: Automation, Sample Management, Automated Cell Technologies, & Scientific Imaging Support. These groups provide technologies, infrastructure, instrumentation, and expertise supporting high-throughput screening, drug discovery, and advanced translational science. The staff scientist (automation lead) will focus on automated platform operation and maintenance while following and contributing to best practices in automated assay execution using industry-standard methodologies. The selected candidate will interact closely with the RSC director, RSC staff members across the various service areas, NCATS scientists (e.g., biologists, chemists, software engineers, informaticians) and our academic collaborators. The selected candidate will contribute to the strategic vision and mentoring of trainees and staff. They will be encouraged to seek NCATS, NIH or external collaborations to further disseminate our data, methods and software.

The candidate will help carry out laboratory experiments utilizing automation and advise on best practices in certain areas (e.g., high-throughput screens, knowledge sources on chemical and biological or disease specific areas). They also will collaborate with engineering staff and researchers on projects requiring custom automation or custom instrumentation. To support translational research efforts, the selected candidate will be part of a broader effort to standardize instrumentation, automation pipelines, and data generated from these systems in a standard format while maintaining documentation and workflows that promote data quality, interoperability, accessibility, and compliance with NIH data-sharing policies.

NCATS expects the selected candidate to create and maintain detailed documentation on all work products to facilitate reuse and collaboration with all DPI scientists. The candidate will contribute to and follow best practices in assay execution, including signal to background and industry standard methodologies. They will serve as the owner and main point of contact for all automated platforms at NCATS and demonstrate a desire and drive to seek out and master novel technologies in this space. They generally will be responsible for training scientists and will take an active role in the greater scientific community to ensure NCATS remains on the cutting edge of scientific advances. The position requires the selected candidate to actively participate in RSC and NCATS committees and meetings and, as appropriate, showcase and collect feedback. The selected candidate will draft manuscripts and publish results in high-impact, peer-reviewed scientific journals and present results at internal and external scientific meetings.

The ideal candidate should possess a doctoral degree (Ph.D., M.D. or equivalent) in mechanical engineering, robotics engineering, biomedical engineering, biology, computer science, or a relevant field and be a recognized expert.

Applicants must have a broad range of high-throughput biological screening and/or high-throughput biochemical experimentation experience that includes at least some of the following:

• Experience required using laboratory automated platforms and associated commercial software, such as Wako/Tecan Director/FlowPilot, HighRes Biosolutions Cellario, Beckman Coulter Tempo and Biosera Green Button Go
• Experience preferred with multi-modal plate readers from various common vendors, such as BMG, Revvity and Molecular Devices
• Experience preferred with liquid handlers, such as Beckman Coulter Echo/i7, HighRes Biosolutions/Let’s Go Robotics BioRAPTR and PreciseDrop, Integra, Wako/Tecan Pin Tool, Agilent Bravo, Multiflow, and EL406.
• Familiarity with programming languages (e.g., Python, C#, C++), machine learning and artificial intelligence (e.g., large language models)
• Familiarity with robotic platform arms in the format of six DOF, SCARA and others

Applicants with knowledge on developing and optimizing cell-based and biochemical assays to support drug discovery and screening efforts are strongly preferred.

Candidates should have demonstrated experience leading laboratory automation initiatives and designing, developing, integrating and deploying automation systems and workflows. Additionally, they should have knowledge on how to translate scientific workflows and research requirements into scalable automation solutions.

Candidates also should have some experience identifying opportunities for process optimization, increased throughput and improved experimental reproducibility through automation.

Candidates should possess:

• Demonstrated scientific accomplishments and a strong publication record
• Excellent analytical and problem-solving skills
• Strong interpersonal, verbal and written communication skills
• Experience working collaboratively in multidisciplinary research environments
• The ability to manage multiple projects and priorities effectively
• A commitment to scientific rigor, reproducibility and innovation