Information Technology, Mathematics and Physics is a subfield within the doctoral programme in Science and Technology at UiS. The subfield has specialisations in cybernetics / signal processing; computer science; physics and mathematics. The doctoral programme is linked to the research within each of these specialisations.
Our research fields
Signal processing involves research into adaptive filtering, signal compression, filterbanks/multirate theory and overcomplete signal representations. There are activities connected with classification and segmentation of images as well as motion estimation in video sequences. Furthermore, applications of signal processing to various signal/image types such as seismic signals, medical images, bio-electrical signals, audio signals, DNA sequences and various signals from measurement systems are addressed.
Cybernetics concentrates on research activities within modelling, identification, simulation, and regulation of various types of processes. Work related to applications in the petroleum and light metal industries and vessel and robot control is also undertaken. Examples of such applications include process monitoring based on state estimation, simulation and regulation of petroleum production pipelines and model-based tuning of industrial robots.
Within computer science, research relates to the development of new, open, and globally distributed information structures. Fundamental theories and methods as well as short term, practical applications and more long-term experimental applications are being explored. Through our research we are seeking to investigate and utilize the interaction between practical challenges in the design of distributed computer systems and new theoretical insights into distributed algorithms.
Within physics, research is carried out in the areas of general theoretical physics, energy and petroleum-related physics and diffraction physics. Within general theoretical physics, work is focussed on mathematical physics, the general theory of relativity, cosmology and astroparticle physics. Within energy and petroleum physics, research is related to modelling and studies in Computational Fluid Dynamics (CFD), non-Newtonian fluids and electromagnetic shielding, mechanical, magnetic, and rheological properties of drilling fluids and flow in porous media. Within diffraction physics, the main activity is associated with X-ray diffraction, theory and experiments, diffuse spread, determining chirality in non-perfect light-atom compounds, studies of nanoparticles deposited in the solid phase and diffractometry.
Research activities within mathematics are mainly in applied mathematics (i.a. differential geometry and the general theory of relativity); mathematical physics and mathematical modelling of fluid flow in porous media; analysis (i.a. multidimensional complex analysis including pluripotential theory and harmonic analysis); algebraic geometry (i.a. geometry of special classes of algebraic varieties and moduli spaces); statistics (i.a. statistical methods for time series analysis, modelling of multivariate dependencies, path analysis, statistical process control, medical statistics and risk and reliability analysis).
The training component should contain the professional and methodological training required for working on and completing the thesis. The programme is structured with a training component (coursework) of 30 credits and a research component of 150 credits. The learning outcomes are partly covered by courses which in turn are divided into three types: programme courses, study courses and project courses, all worth 10 credits each.
These are mandatory for all PhD candidates at the Faculty of Science and Technology.
- DAT911 Foundations of Computer Science (10 credits)
- DAT912 Formal Methods for Specifying Systems (10 credits)
- ELE904 Statistical Signal Processing (10 credits)
- ELE922 Biomedical data analysis (10 credits)
- FYS902 Quantum Particles and Fields on the Lattice (10 credits)
- MAF900 Mathematics and Physical Methods (10 credits)
- MAT900 Fourier and Wavelet Analysis (10 credits)
- MAT901 Functional Analysis with Applications (10 credits)
- MAT910 Topics in Algebraic Geometry (10 credits)
- STA903 General Statistical Methods (10 credits)
Students select one of these topics depending on their chosen specialisation. Study courses from other universities can also be selected as long as the course covers the learning outcomes for the programme.
Project courses are supervisor-led and tailored according to the needs of the PhD project. The following project courses are offered:
- DAT930 PhD Project Course in Computer Science
- ELE920 PhD Project Course in Cybernetics and Signal Processing
- FYS901 PhD Project Course in Physics
- MAT902 PhD Project Course in Mathematics
Learning outcomes will also be covered through completion of research documented by the doctoral thesis, disputation, participation in conferences with presentations, research/study abroad and preparation of scientific papers.
- is at the forefront of knowledge within information technology, physics or mathematics and has mastered the scientific theory, research questions and methods relating to the subject area
- is at the forefront of knowledge within a chosen specialist discipline within the field
- can evaluate the suitability and application of different methods and processes in research and scholarly development projects
- can contribute to the development of new knowledge and theories, methods, interpretations and forms of documentation in the field
- can formulate problems, plan and carry out research and scholarly development work
- can carry out research and scholarly development work of high international standard
- can handle complex academic issues and challenge established knowledge and practices in the field of information technology, physics or mathematics
- can identify new relevant ethical issues and practice their research with scholarly integrity
- can manage complex interdisciplinary assignments and projects
- can communicate research and development work through recognized Norwegian and international channels
- can participate in debates in the field in international forums
- can assess the need for, initiate and practice innovation
To be admitted to the doctoral programme in Science and Technology - Information Technology, Mathematics and Physics, the applicant must normally have minimum a five-year master's degree in technology or mathematical-scientific subjects (the degree specifics are stated in the individual vacancy ads in JobbNorge). The applicant must have a strong academic background with both the master’s thesis grade and the weighted grade average of the master’s degree courses being individually equivalent to or better than a grade B.
As the language of instruction is English, applicants must document that they fulfil the listed English language requirements specified in the ad.
All available PhD vacancies are published here.