Master’s in Healthcare Software & SaMD Engineering
Online master's programme of 1,900 hours in health software and SaMD engineering. 12 modules covering software qualification and classification, clinical requirements, the IEC 62304 life cycle, agile development in regulated environments, software risk management, AI-based software, clinical validation, security, usability and post-market surveillance, with an assigned technical tutor.
Take the controls.
Run a real engineering trade-off from this field. Move the sliders, watch the model react in real time and beat the challenge.
What you will be able to do
Qualify and classify health software under the MDR and IMDRF.
Manage clinical requirements with full traceability.
Develop software in compliance with IEC 62304 using agile practices.
Analyse software-specific risks and their controls.
Document and validate medical artificial intelligence algorithms.
Protect the security and privacy of SaMD platforms.
Plan post-market surveillance for software products.
Who it's for
- Health software engineers.
- Medical software quality managers.
- SaMD regulatory specialists.
- Digital health product owners.
- Software validation engineers.
- Clinical solutions architects.
- Engineering or science graduates looking to enter digital health.
What you'll work with
- Regulation (EU) 2017/745 (medical devices)
- IEC 62304 (medical device software life cycle)
- MDCG 2019-11 (qualification and classification of software)
- ISO 14971 (risk management)
- IEC 82304-1 (health software)
- IEC 81001-5-1 (cybersecurity of health software)
- IEC 62366-1 (usability engineering)
- Regulation (EU) 2024/1689 (artificial intelligence)
- Jira and Confluence
- Polarion ALM
- GitLab CI
- SonarQube
- Python
12 modules · 1900 h
1.1Types of clinical and administrative software1.2SaMD versus software in a device1.3IMDRF definitions for SaMD1.4IMDRF risk categorisation1.5Mobile health and wellness apps1.6Clinical decision support software1.7Digital therapeutics and prescription1.8Business models for health software1.9Market players and digital reimbursement1.10Case study: qualifying five applications
2.1Intended purpose and claims2.2MDCG 2019-11 software qualification2.3Rule 11 of MDR Annex VIII2.4IVD software under Regulation 2017/7462.5Modules and software with mixed functions2.6Wellness software outside the MDR2.7FDA criteria for Clinical Decision Support2.8Decision tools from the Borderline Manual2.9Common classification errors2.10Practical exercise: class justification for a triage algorithm
3.1Capturing the needs of clinical users3.2Functional and safety requirements3.3Traceability between requirements, risks and tests3.4User stories in regulated environments3.5Specification of EHR interfaces3.6Performance and availability requirements3.7Data and algorithm requirements3.8Requirements change management3.9ALM tools for traceability3.10Workshop: traceability matrix for a dosing app
4.1Safety classes A, B and C4.2Software development plan4.3Architectural design and segregation4.4Detailed design and units4.5Unit and integration verification4.6Software system testing4.7Release and version archiving4.8Problem resolution process4.9Maintenance and patches4.10Laboratory: documenting an IEC 62304 release
5.1AAMI TIR45 and agile methodologies5.2Regulatory definition of done5.3Continuous integration and delivery5.4Automated testing and coverage5.5Code review and static analysis5.6Dependency management and SOUP5.7DevOps with quality gates5.8Validation of development tools5.9Documentation generated from code5.10Practical exercise: CI pipeline with regulatory evidence
6.1ISO 14971 applied to software6.2Software-specific hazards6.3Software failure analysis6.4Risk control measures by design6.5IEC/TR 80002-1 as guidance6.6Interoperability risks6.7Algorithm and data risks6.8Residual risk and clinical benefit6.9Updating the risk management file6.10Workshop: risk analysis of a clinical calculator
7.1Model development with clinical data7.2Training, validation and test sets7.3Bias and algorithmic fairness7.4Explainability for clinical users7.5Obligations of the European AI Act for SaMD7.6Predetermined change control plans7.7Performance monitoring in use7.8GMLP good machine learning practice principles7.9Technical documentation of the model7.10Case study: dossier for a retinopathy algorithm
8.1Valid clinical association8.2Analytical or technical validation8.3Clinical performance validation8.4Retrospective and prospective studies8.5Diagnostic metrics and ROC curves8.6Clinical evaluation under MDCG 2020-18.7Real-world evidence8.8Post-market clinical performance follow-up of software8.9Publication and transparency8.10Practical exercise: validation plan for a screening SaMD
9.1IEC 81001-5-1 across the life cycle9.2Cybersecurity under MDCG 2019-169.3Identity and access management9.4Encryption and key management9.5Application penetration testing9.6GDPR and privacy by design9.7Cloud hosting and the Spanish National Security Framework9.8Activity logging and auditing9.9Incident response and notification9.10Laboratory: threat model of a SaMD platform
10.1IEC 62366-1 applied to software10.2Clinical interfaces and cognitive load10.3Alerts and alarm fatigue10.4Integration into care workflows10.5Interoperability with FHIR10.6User training10.7Electronic instructions for use under Regulation (EU) 2021/222610.8Digital accessibility under EN 301 54910.9Managing deployment in hospitals10.10Practical exercise: usability test of an alerts interface
11.1ISO 13485 for software companies11.2IEC 82304-1 standalone health software11.3Vigilance and incident reporting11.4Version management in the field11.5Software recalls and corrections11.6Quality and reliability metrics11.7Notified body audits11.8Registration in EUDAMED11.9FDA pathway for software11.10Case study: managing a critical failure in production
12.1SaMD definition and intended purpose12.2Justified qualification and classification12.3Architecture and development plan12.4Functional software prototype12.5Risk management and cybersecurity12.6Technical and clinical validation12.7Documentation for the technical file12.8Post-market plan for the software12.9Thesis report12.10Master's Thesis: defence before a panel
How you'll learn
Training is 100% online on the SEIUM campus, with downloadable material, recorded classes and an assigned technical tutor. There are no fixed timetables: you progress at your own pace within each intake, so the programme is compatible with full-time work.
Each module combines theory, guided reading of the original standard and applied exercises. The working software is Jira and Confluence, Polarion ALM, GitLab CI, SonarQube and Python, in free, academic or evaluation versions. Work is based on real procedures: development of a software prototype with regulatory evidence, algorithm validation with retrospective clinical data and simulated IEC 62304 life-cycle audits. Assessment is continuous by module, plus the final Master's Thesis.
Standards covered: Regulation (EU) 2017/745, IEC 62304, MDCG 2019-11, ISO 14971, IEC 82304-1, IEC 81001-5-1, IEC 62366-1, Regulation (EU) 2024/1689.
Build it end to end
Your final project follows the real engineering workflow, step by step, reviewed by your tutor.
Where this takes you
Requirements
- University degree in engineering, science or architecture, or equivalent demonstrable professional experience.
- Internet connection and a computer capable of running the programme software.
- English sufficient to read technical standards.
Ready to start?
Send your application today. Our admissions team replies within 72 hours with your study plan and funding options.
Frequently asked questions
The programme totals 1,900 hours over 12–14 months. You set your own pace within each intake, and your tutor helps you plan the workload around your job.
You work with Jira and Confluence, Polarion ALM, GitLab CI, SonarQube and Python, using free, academic or evaluation versions. Your tutor indicates the free alternative wherever one exists.
A SEIUM Institute diploma, awarded on passing the continuous assessment and the Master's Thesis. It is SEIUM's own qualification, not an official state degree; its recognition depends on the programme completed and the regulations of each country.
Yes. Modules passed in a course or postgraduate diploma in the same area are recognised in the higher programme. Ask about the recognition policy when you enrol.
A university degree in engineering, science or architecture (or equivalent professional experience), a computer able to run the programme software and English sufficient to read technical standards.
Start dates are set by SEIUM's faculty for each intake. Our admissions team will confirm the next available date when you apply.
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