Research Scientist/Engineer Assistant

University of Washington•Seattle, WA

About The Position

The Department of Biochemistry has an outstanding opportunity for a Research Scientist/Engineer Assistant to join their team. This position is engaged in the field of spatial omics technology development, specifically focusing on advancing automated manufacturing methods for high-resolution spatial transcriptomics platforms. The work involves integration of bioengineering, robotics, and microfluidics to improve the efficiency and precision of molecular assays. POSITION PURPOSE The research project aims to optimize and automate the fabrication of polony gel arrays for use in spatial transcriptomics. This technology supports the study of tissue architecture at submicron resolution, enabling breakthroughs in understanding molecular mechanisms underlying diseases such as cancer, neurodegenerative disorders, and kidney disease.

Requirements

Bachelors Degree in Electrical Engineering, Mechanical Engineering, Computer Science and Engineering and less than one year of relevant experience, OR combination of education/experience. Equivalent education/experience will substitute for all minimum qualifications except when there are legal requirements, such as a license/certification/registration.
Technical Knowledge: Strong understanding of robotics and automated systems for precision engineering tasks. Basic knowledge of microfluidics and flow cell design.
Software and Programming Skills: Proficiency in programming languages used for robotics, such as Python, MATLAB, or C++. Experience with CAD software (e.g., SolidWorks, AutoCAD) for designing mechanical components.
Problem-Solving Skills: Ability to troubleshoot and optimize robotic workflows and identify performance bottlenecks. Strong analytical skills for interpreting automation data and optimizing system design.
Collaboration and Communication: Effective written and verbal communication skills for documenting processes and collaborating with team members. Ability to work in an interdisciplinary team, integrating input from engineers and biologists.
Attention to Detail: High precision in designing, testing, and implementing automation systems for reproducibility and reliability.

Nice To Haves

Advanced Engineering Knowledge: Expertise in engineering design. Experience with 3D printing for prototyping flow cell designs.
Automation and Robotics Expertise: Familiarity with advanced robotics platforms (e.g., OpenTrons, Beckman Coulter, or Tecan automation systems). Knowledge of machine learning techniques for optimizing robotic workflows (desirable but not essential).
Biology and Chemistry Background: Basic understanding of molecular biology or biochemistry, especially for handling gels, buffers, or related materials.
Interdisciplinary Integration: Prior experience in integrating robotics with biological workflows in a research or industrial setting. Knowledge of spatial omics technologies, including spatial transcriptomics or related high-throughput methods.
Professional Skills: Ability to manage multiple tasks efficiently and work under deadlines. Proactive approach to identifying and solving project challenges.

Responsibilities

Automation of Polony Gel Stamping (50%): Design, fabricate, and test flow cells to streamline gel fabrication. Develop and optimize robotic control systems for automated gel stamping. Troubleshoot and refine automation protocols for reliability and scalability.
System Design and Integration (25%): Collaborate with researchers to design and prototype customized flow cells and robotic components. Integrate hardware and software solutions for seamless operation of the polony gel stamping system.
Data Analysis and Reporting (15%): Collect and analyze data from stamping processes to evaluate performance and reproducibility. Document findings, improvements, and troubleshooting steps to ensure system optimization.
Lab Maintenance and Team Collaboration (10%): Maintain and calibrate automation equipment and ensure proper lab protocols are followed. Work closely with team members to adapt automation systems to emerging research needs.