Master’s in Sensor Calibration and Self-Calibration
Online master's programme of 1,900 hours in sensor calibration and self-calibration. 12 modules covering metrology, measurement uncertainty, laboratory calibration, inertial and perception sensors, online self-calibration, multi-sensor calibration, industrial sensors, machine learning, quality systems and calibration management, applying JCGM 100:2008 (GUM), ISO/IEC 17025 and MATLAB, with an assigned technical tutor.
Master’s in Sensor Calibration and Self-Calibration — studying from Canada
Canada's motorcycle and two-wheeler market is relatively modest compared with the car sector, but it supports a network of dealers, distributors, parts suppliers and recreational riding communities. Manufacturers and importers serve markets across provinces, with seasonal demand shaped by climate. Engineering work in this area includes vehicle homologation, component design and electric two-wheeler development. Regulation of vehicle safety and emissions involves federal and provincial authorities.
Fees for Canada: C$9,230 (Canadian dollar), with instalments and employer sponsorship available.
Relevant bodies in Canada
Typical roles
Questions from Canada
Is this programme recognised by professional bodies in Canada for motorcycle engineering?
SEIUM's qualifications are private, not official state degrees, and are not accredited by any national body in Canada. Vehicle engineering roles in Canada are generally not licensed by a single title-protected body, but employers and industry associations set their own expectations. Transport Canada regulates vehicle safety standards, which is separate from any qualification. Check recognition with prospective employers directly.
What career paths in Canada could this qualification support in the 2-wheeler sector?
Potential roles include design, testing, product development and technical support with motorcycle and powersports manufacturers, distributors and component suppliers. Whether a private qualification is valued is for each employer to decide, and experience often matters most in this sector. The final project can provide a concrete portfolio piece, though it does not guarantee any position.
How can I manage this programme alongside work in Canada?
The programme is entirely online and in English, so it suits students across Canadian time zones, and no student visa is needed to study from home. Workload ranges from 300 to 1,900 hours depending on the programme chosen. Fees are payable in instalments, and employer sponsorship is possible. An assigned technical tutor provides guidance throughout.
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
Apply the concepts of metrology and traceability.
Calculate measurement uncertainty according to the GUM.
Calibrate sensors in the laboratory.
Calibrate inertial and perception sensors.
Design self-calibration algorithms.
Calibrate multi-sensor systems.
Manage calibration programmes within a quality system.
Who it's for
- Calibration engineers
- Metrology technicians
- Sensor fusion engineers
- Perception engineers
- Calibration laboratory managers
- Instrumentation engineers
- Engineering or science graduates looking to move into the automotive and ADAS sector
What you'll work with
- JCGM 100:2008 (GUM) (guide to the expression of uncertainty in measurement)
- ISO/IEC 17025 (competence of testing and calibration laboratories)
- ISO 10012 (measurement management systems)
- JCGM 200:2012 (VIM) (international vocabulary of metrology)
- ISO 16063-21 (vibration calibration by comparison to a reference transducer)
- IEEE 952 (specification and test procedure for fibre-optic gyros)
- ISO 26262 (road vehicle functional safety)
- AIAG MSA (measurement systems analysis)
- MATLAB
- OpenCV
- Kalibr
- ROS 2
- Python
12 modules
1.1International vocabulary of metrology1.2Metrological traceability to standards1.3Accuracy, precision and resolution1.4Systematic and random errors1.5Classification of sensors1.6Transfer functions1.7Non-linearity and hysteresis1.8Time and thermal drift1.9Quality systems in metrology1.10Case study: datasheet of a sensor
2.1The GUM guide to the expression of uncertainty2.2Type A and Type B evaluation2.3Propagation of uncertainties2.4Sensitivity coefficients2.5Expanded uncertainty and coverage2.6Monte Carlo method2.7Uncertainty budgets2.8Conformity with tolerances2.9Decision rules2.10Practical exercise: uncertainty budget for a transducer
3.1Standards and calibration hierarchy3.2Temperature calibration3.3Pressure calibration3.4Force and torque calibration3.5Acceleration calibration3.6Calibration of electrical quantities3.7Calibration intervals3.8Calibration certificates3.9ISO/IEC 17025 accreditation3.10Lab: calibration of a thermocouple
4.1MEMS accelerometers and their errors4.2MEMS and fibre-optic gyroscopes4.3IMU error models4.4Multi-position IMU calibration4.5Rate table calibration4.6Allan variance4.7Magnetometers and hard-iron and soft-iron calibration4.8GNSS sensors and biases4.9Inertial fusion with other sensors4.10Practical exercise: Allan variance of an IMU
5.1Cameras and the pinhole model5.2Intrinsic camera calibration5.3Lens distortion5.4Radar and its calibration5.5LiDAR and error models5.6Ultrasonic proximity sensors5.7Extrinsic calibration between sensors5.8Calibration targets and patterns5.9End-of-line calibration5.10Lab: camera calibration with OpenCV
6.1The self-calibration concept6.2Real-time bias estimation6.3Extended Kalman filters for calibration6.4Calibration using natural motion6.5Targetless calibration6.6Detection of miscalibration6.7Recalibration after maintenance6.8Robustness and observability6.9Limitations of self-calibration6.10Case study: online estimation of IMU biases
7.1Time synchronisation of sensors7.2Camera–LiDAR calibration7.3Radar–camera calibration7.4IMU–camera calibration7.5Least-squares optimisation7.6Kalibr and similar tools7.7Calibration validation7.8Quality metrics7.9Calibration of vehicle fleets7.10Practical exercise: camera–LiDAR calibration
8.1Flow and level sensors8.2Gas analysers8.3Smart sensors and HART8.4On-site calibration of instruments8.5Verification without removal8.6Condition-based maintenance8.7Instrument management in the plant8.8Functional safety of sensors8.9Cybersecurity of instruments8.10Case study: calibration plan for a plant
9.1Data-driven calibration9.2Thermal compensation with neural networks9.3Anomaly detection in sensors9.4Virtual sensor calibration9.5Soft or virtual sensors9.6Transfer between sensors9.7Model explainability9.8Validation of calibration models9.9Integration into embedded systems9.10Lab: thermal compensation with regression
10.1ISO/IEC 17025 in laboratories10.2ISO 10012 for measurement management systems10.3Legal metrology requirements10.4IATF 16949 automotive requirements10.5Measurement system analysis (MSA)10.6Sensor requirements in ADAS10.7Aerospace calibration standards10.8Calibration documentation10.9Metrology audits10.10Workshop: calibration procedure suitable for accreditation
11.1Calibration programmes11.2Equipment management software11.3Calibration costs11.4Outsourcing of calibrations11.5Laboratory indicators11.6Metrological risk management11.7Technician training11.8Trends in sensors11.9Digitalisation of certificates11.10Case study: calibration management for a fleet
12.1Selection of the sensor system12.2Accuracy requirements12.3Error model12.4Calibration procedure12.5Self-calibration algorithm12.6Experimental validation of the system12.7Uncertainty budget12.8Technical conclusions and recommendations12.9Master's Thesis report12.10Master's Thesis: defence before a panel
How you'll learn
100% online training on the SEIUM campus, with downloadable material, recorded classes and an assigned technical tutor. No fixed timetables: you progress at your own pace within each intake, so it can be combined with work.
Each module combines theory, guided reading of the original standard and applied exercises. The working software is MATLAB, OpenCV, Kalibr, ROS 2 and Python, in free, academic or evaluation versions. Testing is studied through real procedures: laboratory sensor calibration, camera–LiDAR multi-sensor calibration and online self-calibration algorithms. Assessment is continuous by module plus the Master's Thesis.
Standards covered: JCGM 100:2008 (GUM), ISO/IEC 17025, ISO 10012, JCGM 200:2012 (VIM), ISO 16063-21, IEEE 952, ISO 26262, AIAG MSA.
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 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 MATLAB, OpenCV, Kalibr, ROS 2 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 demonstrable professional experience.
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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