How can an optical sensor detect the gas leaking into the sea before it becomes a blow-out? How do you kill cancer cells inside the human body with heat while leaving healthy tissue unharmed? Electrical engineering is about developing solutions to the technical challenges of our society. Machine learning, for example, enable face detection in digital cameras and modern spam filters. This Master's degree program gives you a broad education in application of state-of-the-art technology to solve real-world problems.
Electrical Engineering is a discipline of the Master's degree programme in physics.
Electrical engineering provides solutions to the ever-increasing advanced technological demands of modern society. Technology and industry is rapidly developing. Electrical engineering education and competence is at the core of this transition, and will provide a solid foundation for employment in several growth industries. Sensors are essential, for example in medicine and biological research, for new materials, and for oil and gas. This requires knowledge about optics, nanotechnology, transducers, and imaging techniques. In society, there is a virtual explosion of data from websites, images, speech, genes, etc., requiring innovative data analysis based on machine learning, pattern recognition, statistics, and signal- and image analysis implemented in scalable computer programs.
The Electrical Engineering discipline offers specialisation in five different fields of research:
- Microwave techniques
- Machine learning
In Tromsø, electrical engineering education is based on strong research groups covering these fields, the Machine Learning group and the Ultrasound, Microwaves and Optics group. There are good facilities for laboratory work with modern equipment.
Electrical engineering covers a wide range of application areas, some of which are bio-medical physics and imaging, super-resolution optical microscopy/optical nanoscopy, and health analytics:
- Bio-medical physics and imaging research is concentrated on development of new antenna concepts capable of both producing hyperthermia and receiving extremely weak radiated electromagnetic waves containing information on the tissue temperature distribution (microwave radiometry). Hyperthermia is an anti-tumoral therapeutic modality. It consists of selective heating of tumors to temperatures above 42 degrees Celsius, while maintaining healthy tissue nearer to physiological temperatures.
- Optical Nanoscopy research is at the crossroads of Biology and Physics. The group is developing novel fluorescence optical nanoscopy techniques for real-time imaging of sub-cellular organelles (50-100 nm) in living cells. The experimental facilities consist of state-of-the-art commercial high-speed structured illumination microscopy (SIM) and direct stochastic optical reconstruction microscopy (dSTORM) and custom build epi-fluorescence microscopy/nanoscopy based on optical waveguides.
- Health Analytics is focused towards machine learning and data mining in electronic health records (where all the data recorded for each patient in the healthcare system is stored), for personalized medical diagnosis support, for discovering hidden comorbidity patterns, and for decision support for clinicians. Researchers have especially been involved in projects using data from the University Hospital of North Norway related to colorectal cancer and gastrointestinal surgery.
Compulsory courses in the Electrical Engineering discipline:
- FYS-3900 Master's thesis in physics
Students are required to choose at least four of the following 3000-level courses:
- FYS-3007 Microwave techniques
- FYS-3009 Photonics
- FYS-3012 Pattern recognition
- FYS-3024 Biomedical instrumentation and imaging
- FYS-3029 Optical nanoscopy
- FYS-3810 Individual special curriculum
- STA-3001 Computer-intensive statistics
- STA-3002 Multivariable statistical analysis
- STA-3003 Nonparametric inference
Optional courses in the Electrical Engineering discipline may be chosen from those 3000-level courses listed above, that were not chosen among the four required 3000-level courses.
Additional relevant optional courses for Electrical Engineering are:
- FYS-2006 Signal processing
- FYS-2008 Measurement techniques
- FYS-2010 Image analysis
- FYS-2020 Radiation pysics
- FYS-2021 Machine Learning
- FYS-3001 Earth observation from satellites
- FYS-3023 Environmental monitoring from satellite
- FYS-3031 Ultrasound techniques
- FYS-3032 Health data analytics
- FYS-3033 Deep learning
- * AUT-2006 Elektronikk
- * INF-2200 Datamaskinarkitektur og -organisering
- * INF-2201 Operativsystem
- * MAT-2100 Kompleks analyse
- MAT-2200 Differential equations
- MAT-2201 Numerical methods
- MAT-2202 Optimization models
- MAT-2300 Algebra 1
- MAT-3113 Nonlinear partial differential equations
- MAT-3114 Algebraic topology
- MAT-3200 Mathematical methods
- STA-2001 Stochastic processes
- STA-2002 Theoretical statistics
- * STA-2003 Tidsrekker
* = Currently only offered in Norwegian.
Optional courses should be determined in collaboration with your supervisor in connection with choice of research topic in the Master's thesis. Other optional courses may be approved on application or if recommended by your supervisor. An individual special curriculum or project paper may also be part of the degree.
If the Master's thesis involves work in a laboratory, in the field or on a research cruise, it is mandatory to conduct a course in safety education prior to commencing the thesis.
Specializing in electrical engineering at UiT gives you the competence to work with:
- Laboratory Engineering
- Micro and Nanoscopy
- Health Science
- Statistical/Data Analysis
- Machine Learning
|Term||10 ects||10 ects||10 ects|
|First semester (Autumn)||
Obligatory courses (20 ECTS credits)
Optional course (10 ECTS credits)
|Second semester (Spring)||
FYS-3900 Master's thesis in physics (10 of 60 ECTS)
Obligatory course (10 ECTS credits)
Optional course (10 ECTS credits)
|Third semester (Autumn)||
FYS-3900 Master's thesis in physics (20 of 60 ECTS)
Obligatory course (10 ECTS credits)
|Fourth semester (Spring)||
FYS-3900 Master's thesis in physics (30 of 60 ECTS)
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