Internship: Lab Systems
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Questa posizione è in GSK
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Posting Title: Internship: Lab Systems & Automation Intern, IT, 2026 At GSK, we have bold ambitions for patients, aiming to positively impact the health of 2.5 billion people by the end of the decade. Our R&D focuses on discovering and delivering vaccines and medicines, combining our understanding of the immune system with cutting-edge technology to transform people’s lives. We’re uniting science, technology, and talent to get ahead of disease together. Education required: Bachelor’s or Master’s degree in Engineering , Computer Science , Bioinformatics , Biotechnology (with programming skills) or a related technical field. Other requirements:
- Knowledge of programming (Python preferred, or MATLAB)
- Strong interest in laboratory automation, technology and data;
- Curiosity and willingness to learn new tools and systems
- Analytical mindset and problem-solving approach
- Attention to detail and data accuracy
- Good communication skills and ability to work in teams
- Adaptability and proactive attitude
- Support implementation and testing of laboratory automation workflows
- Contribute to integration and configuration of lab instrumentation
- Develop and support basic scripting in Python for workflows and data analysis
- Work on laboratory data collection, cleaning and visualisation (Excel, Power BI)
- Assist with configuration and testing of lab digital tools and systems
- Collaborate with lab scientists, engineers, IT and quality teams
- Identify opportunities for automation and process improvement
- Ensure accurate documentation and compliance with data integrity standards
- Follow lab safety and good laboratory practice requirements
- Hands-on experience with lab automation systems and instrumentation
- Basic development of Python scripts applied to laboratory workflows
- Practical understanding of lab data systems and digital tools
- Data analysis, reporting and dashboard creation
- Exposure to cross-functional collaboration (science, IT, engineering, quality)
- Strong documentation practices and data integrity standards
- Structured problem solving in a technical/scientific environment