Helping enable healthier and safer communities | Clinisys acquired Orchard Software (https://tinyurl.com/clinisysnews)
Project Engineer
Location
France
Posted
2 days ago
Salary
€44.3K - €66.4K / year
Seniority
Senior
Job Description
Project Engineer
Clinisys
• Carry out the installation and configuration of laboratory systems • Integrate software into laboratory workflows (including mapping of daily routines) • Implement LIS projects • Act as a trusted technical contact when working on customer assignments or projects • Contribute to the adoption of emerging technologies, including data-driven and AI-enabled solutions • Work with the Project Manager or Customer Services Manager and follow their guidance and planning • Make proposals and identify technical risks • Prepare execution plans and relevant documentation • Ensure all work is properly documented in internal systems • Deliver assigned tasks according to project plan, budget, and quality standards • Take full responsibility for all technical aspects of assigned tasks • Keep stakeholders informed about progress and risks • Demonstrate flexibility and support on-site customer implementations • Manage and implement small projects or sub-projects • Deliver customer training, including guidance on system data usage and reporting capabilities • Act as interface between customer and development teams • Organize and execute internal and external project handovers • Perform update and upgrade projects
Job Requirements
- Bachelor’s Degree or equivalent
- Alternatively: IT technical training with experience in medical laboratory processes.
- Experience in implementation of LIS / LIMS systems.
- Strong understanding of laboratory processes and organization.
- Knowledge of common IT applications
- Fluency in Dutch and English (French is an asset).
- Basic understanding of AI/ML concepts and their application in healthcare or laboratory environments.
- Ability to work with data flows, data quality, and structured datasets within LIS/LIMS systems.
- Awareness of AI-driven solutions in diagnostics, workflow optimization, or decision support systems.
- Familiarity with data analytics or reporting tools (e.g., dashboards, data extraction, basic analysis) is an asset.
- Ability to interpret data outputs and translate insights into practical recommendations for customers.
- Understanding of data privacy, governance, and ethical considerations related to AI in healthcare environments.
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