Process Manufacturing Engineer developing and implementing PCB manufacturing systems at TTM Technologies. Focused on improving manufacturability and collaborating with customers and suppliers.
About the role
- Lab Informatics Engineer at Lonza designing scalable lab informatics systems. Collaborating with R&D to improve scientific workflows and enhance data management standards.
Responsibilities
- Lead the implementation, configuration, and optimization of laboratory informatics systems (e.g., ELN, LIMS, SDMS) to enhance scientific workflows.
- Partner with R&D scientists to translate experimental processes into structured, scalable digital solutions.
- Design and implement data models, templates, metadata structures, and workflows aligned with FAIR (Findable, Accessible, Interoperable, Reusable) data principles.
- Build and maintain integrations between lab platforms, analytics tools, automation systems, and cloud-based environments using APIs and middleware.
- Develop robust data flows that improve interoperability, reduce manual effort, and ensure high-quality experimental data capture.
- Contribute to digital architecture discussions and help shape the evolution of Lonza’s R&D data ecosystem.
- Deliver user training, documentation, and ongoing support to drive adoption and continuous improvement of digital lab solutions.
Requirements
- MSc (or equivalent) in Bioinformatics, Biology, Chemistry, Engineering, or a related scientific field.
- Experience working within pharma, biotech, or life sciences R&D environments.
- Hands-on experience implementing or optimizing laboratory informatics systems (e.g., ELN, LIMS, SDMS).
- Strong understanding of scientific workflows and experimental data lifecycle management.
- Experience with data modelling concepts and metadata standards; familiarity with FAIR data principles is highly desirable.
- Programming or scripting experience (e.g., Python, R, SQL) and experience integrating systems using APIs (REST, GraphQL).
- Strong communication skills with the ability to collaborate effectively across scientific and technical teams.
- Experience with cloud platforms (Azure, AWS, GCP), laboratory automation systems, or bioinformatics data pipelines would be an advantage.
Benefits
- An agile career and dynamic working culture.
- An inclusive and ethical workplace.
- Compensation programs that recognize high performance.
- A variety of benefits dependent on role and location.
Job title
Job type
Experience level
Salary
Not specified
Degree requirement
Tech skills
Location requirements
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