Automation Specialist
1 week ago
The Automation Associate at the Massachusetts Institute of Technology's Koch Institute for Integrative Cancer Research (KI) within the High Throughput Sciences (HTS) division will play a crucial role in managing automated laboratory systems. This position involves collaborating with leading scientists and engineers to develop automated methodologies that enhance research efficiency and contribute to advancements in cancer treatment.
Key Responsibilities
- Execute project-specific automated workflows tailored to research needs.
- Evaluate equipment requirements and oversee maintenance and repair schedules.
- Provide training for researchers on automation tools and data management.
- Maintain relationships with vendors and manage service agreements.
- Coordinate scheduling for HTS campaigns.
- Implement and oversee analysis software for data interpretation.
- Collaborate with IT to ensure effective data handling.
- Assess new software and hardware for potential integration.
- Monitor and troubleshoot automated systems, ensuring optimal performance.
- Engage in conferences to stay updated on automation trends.
- Uphold safety standards and protocols in all laboratory activities.
- Perform additional duties as required.
Qualifications
Required:
- Bachelor's degree in bioengineering, computer science, chemistry, biology, or a related field.
- Minimum of two years of experience in laboratory automation or related areas (including undergraduate experience).
- Proficiency with automation software (e.g., Freedom Evoware, Cellario).
- Strong attention to detail and the ability to instruct others.
- Excellent organizational, time management, documentation, and communication skills.
- Capacity to adapt to changing priorities in a dynamic environment.
- Discretion and sound judgment regarding confidential information.
Preferred:
- Experience with high-content screening and management of compound or genetic libraries.
- Familiarity with biological data analysis.
- Working knowledge of programming and data science tools such as Python, JavaScript, C#, R, and cloud platforms like Azure, GCP, or AWS.
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