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Medical Research Engineer 80 - 100 % (w/m/d)

Empresa

Hamilton Medical AG

Área de negócios

Research and Development

Local de trabalho

Domat/Ems

Modelo de home office

Up to 20 %

Tipo de contrato

Indefinite Worker

Referência

JR-5973

Technical-Support-Office_HMAG Technical-Support-Office_HMAG

Nossa missão

For more than 40 years, Hamilton Medical has shaped the future of mechanical ventilation. We develop Intelligent Ventilation solutions that support clinicians in critical moments. Our Hamilton ventilators are used in intensive care units, during emergency transport, and in MRI environments. They help medical teams care for adult, pediatric, and neonatal patients worldwide. Here, your work has real impact. Every improvement you make supports better respiratory care for patients around the globe.

How you can make a difference

As a Medical Research Engineer, you join the Clinical Data Science team within Digital Health Solutions, Hamilton Medical's Software as a Medical Device (SaMD) business. Digital Health Solutions develops cloud-based applications including a Clinical Decision Support System (CDSS) for critical care ventilation; our team develops data-driven features and applications for it. You take ownership of your topics in a startup-like setting and help us grow these capabilities further as the products scale. 

Building on a solid understanding of ventilation principles, you design, develop, and validate signal processing and machine learning algorithms that address a wide range of challenges across mechanical ventilation. You own problems from research question through to product-ready solutions, working hands-on with clinical experts and engineers to move prototypes into clinical validation and, ultimately, into products that reach the bedside. 

Your key responsibilities 

  • Design, implement, and rigorously evaluate signal processing, data science, and machine learning algorithms across mechanical ventilation 

  • Take ownership of research topics end-to-end, from problem framing and data exploration to validated, product-oriented solutions 

  • Build and run data analyses and complete ML workflows using our Azure-based cloud data platform 

  • Develop reproducible, well-engineered pipelines that support fast iteration while meeting the traceability and documentation needs of a regulated environment 

  • Work closely with clinical experts, software engineers, and product stakeholders across disciplines 

That’s what you bring along

Must-have 

  • A PhD in a relevant engineering or scientific field (biomedical engineering, computer science, physics, or related), or equivalent industry experience 

  • Several years of experience developing and validating data science / machine learning solutions 

  • Strong programming skills in Python; solid grounding in data and signal processing 

  • Experience with cloud-based data and ML tooling 

  • Analytical, independent, and meticulous work style 

  • Openness to interdisciplinary collaboration and a product-oriented mindset 

Beneficial 

  • Prior experience developing medical-device software, ideally through to production 

  • Working knowledge of Microsoft Azure (Azure Databricks, Azure Machine Learning) 

  • Familiarity with MLOps practices (experiment tracking, model deployment, monitoring) 

How to apply

Learn more about career opportunities at Hamilton at Jobs | Hamilton Medical.

Do you share our values and feel at home in a cooperative, innovative, and down-to-earth environment? At Hamilton, we not only offer a motivating working environment, but also purposeful work and modern working conditions. Our interactions at eye level encourage open communication and a pleasant working environment. Become part of a team where your skills are valued and innovative ideas are fostered. Interested? Then apply online using the "Apply now" button. If you have any questions, please contact us at jobs@hamilton-medical.com with the following details:

Reference: JR-5973-fjm/Contact: Juli Thomann

Applications by post or e-mail can unfortunately not be considered.

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