Master’s in Photorealistic Sensor Simulation and Synthetic Data Engineering
The SEIUM Master's in Photorealistic Sensor Simulation and Synthetic Data Engineering is a 100% online programme of 1900 hours, structured into 13 modules and 128 submodules.
Take the controls.
Run a real engineering trade-off from this programme. Move the sliders, watch the model react in real time and beat the challenge.
What you will be able to do
Master the technical fundamentals of Photorealistic Sensor Simulation and Synthetic Data Engineering and its regulatory vocabulary.
Apply ISO 26262, ISO 21448 (SOTIF) and ISO/SAE 21434 to real-world design and validation decisions.
Build and correlate calculation models with CARLA and IPG CarMaker.
Plan and run test campaigns in ADAS HIL bench and scenario simulator.
Analyse operational data and turn it into engineering decisions.
Prepare the technical and compliance dossier required by the client or the regulator.
Lead a Photorealistic Sensor Simulation and Synthetic Data Engineering project technically from start to finish.
Who it's for
- ADAS engineer looking to specialise in Photorealistic Sensor Simulation and Synthetic Data Engineering.
- SOTIF specialist looking to specialise in Photorealistic Sensor Simulation and Synthetic Data Engineering.
- Perception engineer looking to specialise in Photorealistic Sensor Simulation and Synthetic Data Engineering.
- SDV architect looking to specialise in Photorealistic Sensor Simulation and Synthetic Data Engineering.
- Scenario validation engineer looking to specialise in Photorealistic Sensor Simulation and Synthetic Data Engineering.
- Vehicle cybersecurity specialist looking to specialise in Photorealistic Sensor Simulation and Synthetic Data Engineering.
- Engineering or science graduates looking to move into manufacturers.
What you'll work with
- ISO 26262
- ISO 21448 (SOTIF)
- ISO/SAE 21434
- UNECE R157 (ALKS)
- UNECE R155 and R156
- SAE J3016 (levels of driving automation)
- ASAM OpenSCENARIO
- ASAM OpenDRIVE
- AUTOSAR Adaptive
10 modules · 1900 h
1.1Key concepts and quantities of Photorealistic Sensor Simulation and Synthetic Data Engineering1.2Technology landscape and state of the art1.3Technical terminology and reference documentation1.4Physical principles applied to Photorealistic Sensor Simulation and Synthetic Data Engineering1.5Functional architecture: from requirements to components1.6Typical use cases in manufacturers1.7Common errors and diagnostic criteria1.8Interfaces with other engineering disciplines1.9Critical reading of client specifications1.10Kick-off workshop: scope and requirements
2.1Applicable regulatory framework: overview2.2ISO/SAE 21434: scope and obligations2.3UNECE R157 (ALKS): structure and critical points2.4UNECE R155 and R156 in project practice2.5SAE J3016 (levels of driving automation): acceptance criteria and evidence2.6Regulatory hierarchy and conflicts between standards2.7Compliance dossier: structure and traceability2.8Internal audit and evidence preparation2.9Legal responsibilities and penalty regime2.10Workshop: requirement-standard-evidence mapping
3.1Model set-up: assumptions and simplifications3.2ROS 2: environment, workflow and best practice3.3MATLAB/Simulink applied to Photorealistic Sensor Simulation and Synthetic Data Engineering3.4Meshing, discretisation and convergence control3.5Boundary conditions and load cases3.6Sensitivity analysis and parametric study3.7Model verification against analytical solution3.8Correlation with experimental data3.9Automation and scripting of calculation campaigns3.10Workshop: complete model of a Photorealistic Sensor Simulation and Synthetic Data Engineering case
4.1Implicit and explicit methods: selection criteria4.2Numerical stability and time-step control4.3Reduced-order models (ROM) and surrogates4.4Multi-objective optimisation and Pareto fronts4.5Uncertainty quantification and error propagation4.6Design of experiments (DoE) applied to simulation4.7Co-simulation and multiphysics coupling4.8High-performance computing: parallelisation and queues4.9Version management and calculation reproducibility4.10Workshop: model-test correlation
5.1Requirements capture and management5.2Functional breakdown and allocation to subsystems5.3Interface matrix and configuration control5.4Design criteria and project margins5.5Analysis of alternatives and technical justification5.6Design documentation: drawings, reports and ECNs5.7Design reviews: PDR and CDR5.8Change management and version control5.9Design for manufacture, assembly and service (DfX)5.10Workshop: architecture of a Photorealistic Sensor Simulation and Synthetic Data Engineering system
6.1Material selection and trade-off criteria6.2Mechanical properties and in-service behaviour6.3Manufacturing processes applicable to Photorealistic Sensor Simulation and Synthetic Data Engineering6.4Joints, interfaces and tolerances6.5Surface treatments and corrosion protection6.6Degradation, fatigue and service life6.7Supply chain and supplier qualification6.8Dimensional control and metrology6.9Batch traceability and material documentation6.10Workshop: material selection for a Photorealistic Sensor Simulation and Synthetic Data Engineering component
7.1Test plan: objectives, scope and resources7.2Instrumentation and measurement chain7.3vehicle cybersecurity laboratory: procedure and limitations7.4ADAS HIL bench: set-up, acquisition and analysis7.5Measurement uncertainty and repeatability7.6Acceptance testing versus development testing7.7Test failure analysis and corrective actions7.8Test reports and validity of results7.9Test-simulation correlation and model closure7.10Workshop: Photorealistic Sensor Simulation and Synthetic Data Engineering validation campaign
8.1Data acquisition and storage architecture8.2Data quality: cleaning, gaps and outliers8.3Time series and frequency analysis8.4Technical visualisation and dashboards8.5Statistical methods applied to Photorealistic Sensor Simulation and Synthetic Data Engineering8.6Introduction to machine learning in the domain8.7Condition-based predictive maintenance8.8Data governance, privacy and security8.9Report automation and reproducibility8.10Workshop: analytics on a real Photorealistic Sensor Simulation and Synthetic Data Engineering dataset
9.1Reliability, availability, maintainability and safety9.2Functional hazard analysis and risk classification9.3FMEA and FMECA: method and application9.4Fault trees and root cause analysis9.5Allocation of reliability targets and budgets9.6Barriers, redundancies and degraded modes9.7Functional safety: from requirement to evidence9.8System cybersecurity and attack surface9.9Non-conformity management and CAPA actions9.10Workshop: safety case for a Photorealistic Sensor Simulation and Synthetic Data Engineering system
10.1Commissioning and acceptance protocols10.2Preventive and predictive maintenance plan10.3Spare parts and obsolescence management10.4In-service monitoring and indicators10.5Life extension and refurbishment10.6Incident and availability management10.7Operator training and user documentation10.8Withdrawal, decommissioning and second life10.9Life cycle costs (LCC)10.10Workshop: operation and maintenance plan for Photorealistic Sensor Simulation and Synthetic Data Engineering- Module 11 — Sustainability, LCA and project economics (146 h)
11.1Life cycle assessment (LCA): method and scope11.2Product and process carbon footprint11.3Circular economy applied to Photorealistic Sensor Simulation and Synthetic Data Engineering11.4Energy and material efficiency11.5Environmental regulatory framework and reporting11.6ESG criteria in technical decisions11.7Total cost of ownership and business case11.8Project financing and public funding11.9Technical communication of sustainability results11.10Workshop: simplified LCA of Photorealistic Sensor Simulation and Synthetic Data Engineering- Module 12 — Technical project management and transfer (146 h)
12.1Planning, scope and work breakdown structure12.2Cost estimation and variance control12.3Project risk management12.4Technical procurement and tender specifications12.5Industrial property and protection of results12.6Multidisciplinary teams and technical communication12.7Transfer of results and industrialisation12.8Project metrics and close-out12.9Professional ethics and engineering responsibility12.10Workshop: project plan for Photorealistic Sensor Simulation and Synthetic Data Engineering- Module 13 — Master's thesis (146 h)
13.1Topic definition and work plan13.2State of the art and literature review13.3Methodology and validation plan13.4Supervised technical development13.5Analysis of results and discussion13.6Compliance dossier or safety case13.7Final report and document standardisation13.8Defence before an examining panel
How you'll learn
100% online training on the SEIUM campus, with downloadable materials, recorded classes and a dedicated technical tutor. No fixed timetable: students progress at their own pace within the intake period, making it easy to combine with work.
Each module combines theory, guided reading of the original standards and applied exercises. The software used is CARLA, IPG CarMaker, dSPACE ASM, ROS 2, MATLAB/Simulink, in free, academic or trial versions. Testing is studied through real procedures from ADAS HIL bench, scenario simulator, test track. Assessment is continuous for each module, plus the final Master's thesis.
Build it end to end
Your final project follows the real engineering workflow, step by step, reviewed by your tutor.
Master the technical fundamentals of Photorealistic Sensor Simulation and Synthetic Data Engineering and its regulatory vocabulary.
Apply ISO 26262, ISO 21448 (SOTIF) and ISO/SAE 21434 to real-world design and validation decisions.
Build and correlate calculation models with CARLA and IPG CarMaker.
Plan and run test campaigns in ADAS HIL bench and scenario simulator.
Analyse operational data and turn it into engineering decisions.
Where this takes you
Requirements
- A university degree in engineering, science or architecture, or equivalent proven professional experience.
- An internet connection and a computer able to run the programme software.
- A level of 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 1900 hours spread over 12 to 18 months. That is an average of 10 to 15 hours per week, compatible with a full-time job.
You will work with CARLA, IPG CarMaker, dSPACE ASM, ROS 2. Free, academic or trial versions are used, and your tutor will point out a free alternative where 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-accredited degree.
Yes. Modules passed in a course or postgraduate diploma in the same area are recognised in the higher programme. Check the recognition policy when you enrol.
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