Master’s in Validation, Simulation & Data Engineering
Online master's programme of 1,900 hours in validation, simulation and data engineering, structured in 12 modules covering scenario-based validation, ASAM OpenSCENARIO and OpenDRIVE, vehicle, traffic and sensor simulation, X-in-the-loop testing, track and road testing, validation data management, re-injection, metrics and acceptance criteria and type approval under ISO 34502, with an assigned technical tutor.
Master’s in Validation, Simulation & Data Engineering — studying from the United Kingdom
The UK is developing a strong position in autonomous vehicles and advanced driver assistance systems, supported by testbeds such as the Connected and Autonomous Vehicle sites and the Automated Vehicles Act framework. Automotive manufacturers, Tier 1 suppliers and technology firms work on sensor fusion, perception, functional safety and vehicle software architectures. Centres in the Midlands, the North and Scotland host research collaborations between universities and industry. Demand is growing for engineers who combine embedded software, machine learning and vehicle systems knowledge to build software-defined vehicles.
Fees for the United Kingdom: £7,440 (Pound sterling), with instalments and employer sponsorship available.
Relevant bodies in the United Kingdom
Typical roles
Questions from the United Kingdom
What UK professional bodies relate to autonomous vehicle and ADAS engineering?
Relevant UK bodies include the Institution of Engineering and Technology (IET), the British Computer Society (BCS) for software, and the Institution of Mechanical Engineers (IMechE). Professional registration is managed through the Engineering Council. SEIUM's qualifications are private and not accredited by these bodies, so recognition is for employers or the relevant body to decide. Contact the IET or BCS to check how your study would be considered.
Do UK automotive and technology employers hire people with private qualifications in autonomy and ADAS?
UK employers in autonomous and ADAS development, including vehicle manufacturers, Tier 1 suppliers and software firms, usually focus on technical skill, project experience and the ability to work on safety-critical systems. A private qualification may help show your specialist knowledge, but how it is valued depends on each employer. Evidence of practical work, such as simulation or coding projects, is often more decisive.
How much time will this take alongside a UK job, and what language level do I need?
Programmes are fully online and taught in English, so you need strong technical English reading and writing skills. Because there is no need for a student visa to study from home, you can keep your current UK role while studying. Each programme has a defined number of hours, and you will be assigned a technical tutor. Compare the hours with your schedule and ask about employer funding options before committing.
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
Design scenario-based validation strategies.
Model scenarios using ASAM standards.
Configure vehicle, traffic and sensor simulation environments.
Plan X-in-the-loop, track and road testing.
Manage validation data and re-injection.
Define metrics and acceptance criteria.
Develop a complete validation and simulation project.
Who it's for
- Autonomous systems validation engineers designing scenario-based test strategies.
- Simulation engineers working with CARLA, CarMaker, SUMO or VTD.
- Scenario engineers modelling cases in OpenSCENARIO and OpenDRIVE.
- Validation data engineers managing fleet logs, mining and re-injection.
- HIL test engineers running X-in-the-loop campaigns.
- ADS type-approval managers preparing evidence for NATM and R157.
- Engineering or science graduates aiming to enter the automotive sector.
What you'll work with
- ISO 34502 (scenario-based safety evaluation framework)
- ASAM OpenSCENARIO (dynamic scenario description)
- ASAM OpenDRIVE (road network description)
- ISO 21448 (safety of the intended functionality, SOTIF)
- UN ECE R157 (Automated Lane Keeping Systems)
- Implementing Regulation (EU) 2022/1426 (type approval of automated driving systems)
- ISO 34501 (terms and definitions for test scenarios)
- ASAM OSI (Open Simulation Interface)
- CARLA
- IPG CarMaker
- SUMO
- dSPACE
- Foxglove Studio
12 modules · 1900 h
1.1The autonomous driving validation problem1.2Limitations of mileage as a metric1.3Scenario-based approaches1.4The virtual-physical testing pyramid1.5Relationship with SOTIF and ISO 262621.6Regulatory validation frameworks1.7The PEGASUS and VVM programmes1.8Safety and performance metrics1.9Organising validation1.10Case study: validation strategy for an ALKS
2.1Functional, logical and concrete scenarios2.2The ASAM OpenSCENARIO XML format2.3The OpenSCENARIO DSL 2.x language2.4Road networks with OpenDRIVE2.5Scenario databases2.6Parameterisation and search spaces2.7Scenarios from real-world data2.8R157 regulatory scenarios2.9The ISO 34501 and 34502 standards2.10Lab: cut-in scenario in OpenSCENARIO
3.1Simulator architecture3.2The CARLA, CarMaker and VTD simulators3.3Vehicle dynamics models3.4Traffic models with SUMO3.5Co-simulation with FMI3.6OSI sensor interfaces3.7Determinism and reproducibility3.8Scaling in the cloud3.9Simulation credibility3.10Practical exercise: CARLA and SUMO co-simulation
4.1Ideal, phenomenological and physical models4.2Ray tracing for camera and LiDAR4.3Radar models4.4The sim-to-real gap4.5Validation of sensor models4.6Synthetic data for training4.7Neural rendering with NeRF and Gaussian splatting4.8Computational cost of physics-based simulation4.9Commercial sensor simulation tools4.10Workshop: LiDAR model with noise
5.1Model-in-the-loop (MIL) testing5.2Software-in-the-loop (SIL) testing5.3Hardware-in-the-loop (HIL) testing5.4Vehicle-in-the-loop (ViL) testing5.5Driver-in-the-loop testing with a simulator5.6Sensor data injection5.7Real-time synchronisation5.8Test bench management5.9Campaign automation5.10Lab: HIL bench with dSPACE
6.1Design of track tests6.2Moving targets and platforms6.3Open-road testing6.4Management of safety drivers6.5Instrumentation and ground truth6.6Safety during testing6.7Permits for testing on public roads6.8Physical reproducibility of manoeuvres6.9Correlation with simulation6.10Practical exercise: track test protocol
7.1Data lake architecture7.2Ingestion of fleet data7.3The rosbag and MCAP formats7.4Data catalogues and search7.5Labelling and annotation7.6Scenario mining7.7Data quality7.8Governance and privacy7.9Storage costs7.10Workshop: scenario search in logs
8.1Playback of recorded data8.2Open-loop re-injection8.3Closed-loop re-simulation8.4Editing recorded scenes8.5Software version management8.6Regression assessment8.7Comparison between versions8.8Scaling re-injection8.9Limitations of open-loop testing8.10Lab: re-injection with MCAP
9.1Criticality metrics TTC and PET9.2Rule compliance metrics9.3Comfort metrics9.4Pass/fail criteria9.5Aggregated residual risk9.6Comparison with a human driver9.7Coverage metrics9.8Validation dashboards9.9Statistical interpretation of results9.10Practical exercise: calculation of criticality metrics
10.1Credibility of simulation tools10.2Tool qualification under ISO 2626210.3Model validation10.4Uncertainty management10.5Traceability from requirements to tests10.6Verification processes10.7Validation audits10.8Applicable quality standards10.9Documentation for type approval10.10Case study: simulator credibility report
11.1New assessment/test methods (NATM)11.2Regulation R157 and test annexes11.3EU regulation on automated systems11.4Audit and virtual testing11.5Track testing for type approval11.6In-service monitoring11.7The ISO 34505 standard11.8Authorities' experiences11.9Regulatory trends in validation11.10Workshop: validation plan according to NATM
12.1Definition of the system and ODD12.2Design of the validation strategy12.3Building the scenario database12.4Configuring the simulation environment12.5X-in-the-loop test plan12.6Data and metrics management12.7Analysis of results12.8Conclusions and future work12.9Thesis 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 the intake, so the programme can be combined with work.
Each module combines theory, guided reading of the original standard and applied exercises. The working software is CARLA, IPG CarMaker, SUMO, dSPACE and Foxglove Studio, in free, academic or evaluation versions. Exercises are based on real procedures for large-scale scenario simulation, HIL testing of automated functions and track testing with moving targets. Assessment is continuous by module, plus the final Master's Thesis.
Standards covered: ISO 34502, ASAM OpenSCENARIO, ASAM OpenDRIVE, ISO 21448, UN ECE R157, Implementing Regulation (EU) 2022/1426 (ADS), ISO 34501, ASAM OSI.
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
- A university degree in engineering, science or architecture, or equivalent demonstrable professional experience.
- An internet connection and a computer capable of running the programme's 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 CARLA, IPG CarMaker, SUMO, dSPACE and Foxglove Studio, 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's 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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