Do you want to join us in shaping the future of agriculture?
We are seeking a highly skilled Genotyping Logistics Engineer to join our innovative research team. The ideal candidate will be responsible for driving operational excellence in the genotyping laboratory by optimizing workflows, enhancing efficiency, and establishing the labs as few center of excellence facilities. The role focuses on implementing process improvements, leveraging automation, and simplifying workflows to ensure high-quality, scalable, and cost-effective genotyping processes.
Accountabilities:
- Process Optimization: Analyze existing genotyping lab processes to identify bottlenecks, inefficiencies, and areas for improvement. Design and implement optimized workflows to enhance throughput, reduce turnaround times, and improve accuracy. Apply Lean, Six Sigma, and other process improvement methodologies to eliminate waste and streamline operations.
- Process Excellence: Establish and monitor key performance indicators (KPIs) to track lab efficiency, quality, and productivity. Lead continuous improvement initiatives to maintain high standards of operational excellence. Develop standard operating procedures (SOPs) to ensure consistency and compliance with industry standards.
- Workflow Optimization: Redesign lab workflows to improve sample handling, data processing, and result delivery. Collaborate with cross-functional teams to integrate new technologies and methodologies into existing workflows. Ensure workflows are scalable to accommodate increased sample volumes and evolving genotyping demands.
- Future Workflow Recommendations: Research and recommend automation solutions to simplify and accelerate genotyping processes. Propose innovative workflows that leverage cutting-edge technologies, such as robotic process automation (RPA) and advanced data analytics. Develop a roadmap for transitioning manual processes to automated systems while maintaining quality and reliability.
- Shift Development and Implementation: Design and Implement shift schedules to maximize lab-efficiency, ensuring optimal coverage for high-throughput genotyping operations. Analyze lab workload patterns to align staffing levels with peak processing times, minimizing downtime and overtime costs. Collaborate with Lab operations to develop flexible shift structures that support potential 24/7 operations and accommodate automation schedules.
- Stakeholder Collaboration: Work closely with lab scientists, automation engineers, data analysts, and leadership to align process improvements with organizational goals. Provide training and guidance to lab staff on new processes, tools, and technologies. Communicate progress and outcomes of optimization initiatives to senior leadership.