Senior Research Associate- NGS

Job description

**ABOUT US:** Volta Labs is an applications company that is revolutionizing the future of genomics. We are a Boston based, venture-backed biotech startup that makes extracting vital information from biological samples is as simple as pressing a button, through our flagship product Callisto. Our product speeds up processing time for scientists and increases accessibility to important genetic information for patients. Sitting at the intersection of science and engineering, we invite you to join us on our journey to shape the future of genomics, where insatiable curiosity is encouraged and every Voltarian makes an impact. **THE TEAM:** You'll join a team of innovative thinkers who love to experiment, collaborate, and win together. We are passionate about pushing the boundaries of automation, biology, computing, robotics, design, and user experience to benefit our customers and the world. Reporting to a Senior Scientist on the team, you will participate in the design and development of genomics sample prep applications. Volta is building a suite of genomics applications for its disruptive digital fluidics sample prep automation platform. We are seeking an energetic, detail-oriented and collaborative individual with a desire to learn and participate in product development in an industry setting. Beyond executing established protocols, this role is ideal for someone who enjoys tinkering—asking why things work the way they do, experimenting thoughtfully, and improving workflows from first principles. You’ll encounter day-to-day experimental and operational challenges where curiosity, creativity, and practical problem-solving matter as much as prior experience. ### Day 1 to Year 1 - Execute experiments following good laboratory practice and standard protocols - Thoroughly document all procedures, data and observations in an electronic lab notebook - Summarize, present and discuss findings in team meetings - Actively participate in experimental design, data analysis, and report writing - Proactively identify inefficiencies, experimental bottlenecks, or recurring issues in lab workflows and propose practical improvements - Use available tools (including scripting, spreadsheets, or AI-assisted workflows) to automate repetitive tasks, improve data handling, and increase experimental efficiency - Assist with reagent ordering, inventory, equipment maintenance and general laboratory dutiesMaintain a clean work area and equipment in proper working order **Within the first 3 months, you’ll…** - Ramp up on the Callisto platform, associated genomics workflows, and internal tools. - Learn and execute core sample prep, library prep, QC, and NGS applications under guidance from senior team members. - Become comfortable with lab standards, documentation practices, and data analysis workflows. - Begin contributing to experiments, troubleshooting efforts, and workflow optimization discussions. - Shadow more experienced team members during experimental design reviews, troubleshooting sessions, or internal demos **Within 6 months you’ll…** - Independently execute and troubleshoot experiments across one or more applications. - Contribute meaningfully to workflow optimization efforts by identifying bottlenecks, proposing improvements, and validating changes experimentally. - Use scripting, spreadsheets, or AI-assisted tools to streamline repetitive tasks, data handling, or documentation workflows. - Help create and refine internal protocols, setup guides, and experimental documentation to improve reproducibility and team efficiency. - Confidently present data, insights, and recommendations in team meetings and cross-functional discussions. **At 12+ months you’ll…** - Operate as a trusted technical contributor within the Applications team, owning experiments or sub-workflows end-to-end. - Serve as a go-to resource for specific assays, workflows, or troubleshooting areas. - Help establish best practices for experimental execution, documentation, and workflow optimization. - Mentor newer team members through onboarding, experimental execution, or problem-solving approaches. - Continue improving how work gets done—whether through better experiments, clearer documentation, or smarter use of tools