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Computational Engineering, Master's Degree Programme (M-COMPEN)

Facts
Studieprogramkode

M-COMPEN

Vekting (SP)

120

Studienivå

Master's degree (2 years)

Fører til grad

Master of Science

Varighet

4 Semesters

Grunnstudium

No

Undervisningsspråk

English

Learning outcomes

After having completed the master’s programme in Computational Engineering, the student shall have acquired the following learning outcomes, in terms of knowledge, skills and general competence:

Knowledge

K1: Has advanced knowledge in the field of uncertainty quantification and modeling for decision support. This means that the candidate has the ability to develop mathematical models that account for uncertainties contained in incomplete data and information and provide the basis for improved understanding and interpretation of data as well as for decision support.

K2: Advanced knowledge of effective methods for designing, developing and testing models.

K3: Advanced knowledge in the use of algorithms and computational thinking to solve discrete and continuous problems.

K4: Understand the limitations introduced by representing a complex system with a model.

K5: Understand the constraints associated with the chosen solution method, including approximation errors and constraints linked to the selection of specific algorithms or numerical methods.

K6: Understand the importance of quantifying relevant and material uncertainties to generate insight and informed decisions.

K7: Deep understanding of the significance and consequences imbedded in the well-known quote: “All models are wrong, but some models are useful” (George Box, 1978).

Skills

S1: Analyze and act critically to different sources of information and apply them to structure and formulate professional and scientific reasoning according to modeling, uncertainty quantification, simulation, optimization and decision support.

S2: Detailed knowledge and experience of programming in at least one high level programming language.

S3: Determine model parameters using data and expert knowledge.

S4: Be able to find the right balance between a model's usefulness (how credible is the understanding generated by the model) and manageability (any analysis must be completed within given time and resource constraints).

S5: Develop custom modeling programmes for specific decision- or optimization situations.

S6: Model systems and develop new instruments and applications for gathering relevant data, analysis and management in accordance with established engineering principles.

S7: Evaluate instruments and applications to quantify the value of information and to optimize the data gathering, analysis and management.

S8: Perform sensitivity analysis of model parameters to generate additional insights and understanding.

General Competence

G1: Develop hypotheses and suggest systematic ways to test these using mathematical models.

G2: Communicate in a professional way about scientific problems, decisions, results of data, uncertainty, and modeling analysis - both to specialists and to the general public.

G3: Utilize the generic nature that lies in the use of mathematical formulations to actively seek to transfer knowledge between different applications.

G4: Utilize the mathematical formulation to gain insight into the core of the problem that is uncover the most basic mechanisms that govern the process being studied.

G5: Insight into “The Art and Science of Mathematical Modeling”.

Intro

A master’s degree in Computational Engineering makes you eligible for the most demanding and interesting tasks in the private or public sector as an engineer, researcher or leader. You will acquire skills that will enable you to analyse complex real world problems, and to use this insight as a foundation for better decisions to, for example, improve performance, quality, and workflows. The career opportunities are multiple and in a world where digitalization is becoming increasingly important there is a need for candidates with domain knowledge and computational modeling skills. Many companies, including all major oil, service companies, research institutes and many of their spin-off companies seek this competence. The programme is international, where Norwegian and foreign students study jointly. All of the courses are taught in English. The Master programme introduces, illustrates, and discusses a methodology that builds on mathematics, statistics and basic programming from a Bachelor program in engineering or science. The programme includes advanced topics in modeling and algorithms, decision analysis, optimization, and uncertainty quantification.

Mater in Computational Engineering is a post-graduate programme that runs over four semesters and covers 120 ECTS, resulting in a master’s degree in computational engineering

Course assessment

Degree programmes and courses are revised annually. Evaluation are a central component of the UiS quality system. Courses in the degree are subject to student evaluation, in accordance with the University’s evaluation system.

Career prospects

Modeling skills and abilities are necessary in almost every industry. Some examples of industries and businesses where students can find employment are: Oil and energy, consulting and service companies, hospitals and other public agencies. The use of digital technology is rapidly increasing and can be seen everywhere. Computational Engineers are absolutely crucial in realizing the information society, because they have specific knowledge of the engineering aspects (domain knowledge) and computational skills to take the necessary digitalization steps. 

Contact information

Study Coordinator:   Karina Sanni   Email: karina.sanni@uis.no / Tel: +47 51 83 11 45 

Study Programme Leader/Academic staff: Aksel Hiorth aksel.hiorth@uis.no / Tel: +47 51 83 17 57

Professor Reidar Brumer Bratvold. Email: reidar.bratvold@uis.no / Tel: +47 51 83 22 60

Professor Steinar Evje. Email: steinar.evje@uis.no /  Tel. +47 51 83 17 41

Study plan and courses
  • Compulsory courses

    • Master's Thesis in Computational Engineering

      Year 2, semester 3

      Master's Thesis in Computational Engineering

      Study points: 30

  • 3rd semester at UiS or Exchange Studies

    • Courses at UiS 3rd semester

    • Exchange 3rd semester

  • Compulsory courses

    • Modeling for Decision Insight

      Year 1, semester 1

      Modeling for Decision Insight

      Study points: 10

    • Modeling and Computational Engineering

      Year 1, semester 1

      Modeling and Computational Engineering

      Study points: 10

    • Mathematical and Numerical Modelling of Conservation Laws

      Year 1, semester 2

      Mathematical and Numerical Modelling of Conservation Laws

      Study points: 10

    • Master's Thesis in Computational Engineering

      Year 2, semester 3

      Master's Thesis in Computational Engineering

      Study points: 30

  • Choose one course in 2nd semester

    • Applied Data Analytics and Statistics for Spatial and Temporal Modeling

      Year 1, semester 2

      Applied Data Analytics and Statistics for Spatial and Temporal Modeling

      Study points: 10

    • Modeling and control for automation processes

      Year 1, semester 2

      Modeling and control for automation processes

      Study points: 10

  • Elective courses

    • Introduction to data science

      Year 1, semester 1

      Introduction to data science

      Study points: 10

    • Economics and Decision Analysis for Engineers

      Year 1, semester 1

      Economics and Decision Analysis for Engineers

      Study points: 10

    • Applied Data Analytics and Statistics for Spatial and Temporal Modeling

      Year 1, semester 2

      Applied Data Analytics and Statistics for Spatial and Temporal Modeling

      Study points: 10

    • Computational Fluid Dynamics (CFD)

      Year 1, semester 2

      Computational Fluid Dynamics (CFD)

      Study points: 10

    • Integrated Reservoir Management From Seismic Field Development Planning

      Year 1, semester 2

      Integrated Reservoir Management From Seismic Field Development Planning

      Study points: 10

  • Other elective courses 1st and 2nd semester

  • 3rd semester at UiS or Exchange Studies

    • Courses at UiS 3rd semester

      • Elective courses 3rd semester

        • Reservoir modelling and simulation  

          Year 2, semester 3

          Reservoir modelling and simulation  

          Study points: 10

        • Developing Research and Presentation Skills

          Year 2, semester 3

          Developing Research and Presentation Skills

          Study points: 10

        • Economics and Decision Analysis for Engineers

          Year 2, semester 3

          Economics and Decision Analysis for Engineers

          Study points: 10

        • Statistical learning

          Year 2, semester 3

          Statistical learning

          Study points: 10

      • Other elective courses 3rd semester

        • Discrete Simulation and Performance Analysis

          Year 2, semester 3

          Discrete Simulation and Performance Analysis

          Study points: 10

        • Introduction to data science

          Year 2, semester 3

          Introduction to data science

          Study points: 10

        • Finite Element Methods, Advanced Course

          Year 2, semester 3

          Finite Element Methods, Advanced Course

          Study points: 10

        • Statistical modeling and simulation

          Year 2, semester 3

          Statistical modeling and simulation

          Study points: 10

    • Exchange 3rd semester

Student exchange

Exchange semester
Semester 3

Exchange scheme
In semester 3 of the Master program in Computational Engineering, you have the possibility to study abroad at one of UiS partner universities. This semester has 30 ECTS elective courses.

When going abroad, you must choose courses that comprise a similar specialization within your field, and these must be pre-approved before you leave. It is also important that the courses you are going to take abroad do not overlap in content with the courses you have taken or will take later in the study program. A good tip is to think about your specialization and your field of interest.

It is recommended to start planning the exchange early.

More possibilities
In addition to the recommended universities listed below, UiS has a number of agreements with universities outside Europe that are applicable to all students at UiS, provided that they find a relevant subject offering. 

Within the Nordic region, all students can use the Nordlys and Nordtek networks. Find out more.  

Contact person
Guidance and pre-approval of courses:
Karina Sanni

General information about exchange: Exchange guide in Digital student service desk

Student exchange
  • All countries

    Aalborg Universitet

    Aalborg Universitet (AAU) er kjent for å benytte seg av problembasert læring i grupper, noe som kan by på en spennende læringsprosess.

    Colorado School of Mines

    Colorado School of Mines (CSM) er et offentlig universitet kjent verden over for sin gode ingeniørutdannelse.

    Griffith University

    Griffith University er en populær utvekslingsdestinasjon for UiS-studenter. Universitetet er et særlig godt valg for studenter innen musikk/dans, hotell/turisme og business.

    Politecnico di Milano University

    Politecnico di Milano er Italias største tekniske universitet med om lag 40.000 studenter og er høyt rangert på en rekke internasjonale rankinglister.

    Technical University of Munich

    The Technical University of Munich, also known as TUM, accounts for major advancements in the field of natural sciences. TUM is one of the best universities in Germany and has several awarded scientists and Nobel Prize winners. The Technical University of Munich strives for excellent teaching and research quality.

    Uppsala universitet

    “In Uppsala you walk in the gardens of Linnaeus, follow in the footsteps of Nobel laureates, and at the same time meet today’s and tomorrow’s smartest teachers and researchers.”

  • Australia

    Griffith University

    Griffith University er en populær utvekslingsdestinasjon for UiS-studenter. Universitetet er et særlig godt valg for studenter innen musikk/dans, hotell/turisme og business.

  • Denmark

    Aalborg Universitet

    Aalborg Universitet (AAU) er kjent for å benytte seg av problembasert læring i grupper, noe som kan by på en spennende læringsprosess.

  • Germany

    Technical University of Munich

    The Technical University of Munich, also known as TUM, accounts for major advancements in the field of natural sciences. TUM is one of the best universities in Germany and has several awarded scientists and Nobel Prize winners. The Technical University of Munich strives for excellent teaching and research quality.

  • Italy

    Politecnico di Milano University

    Politecnico di Milano er Italias største tekniske universitet med om lag 40.000 studenter og er høyt rangert på en rekke internasjonale rankinglister.

  • Sweden

    Uppsala universitet

    “In Uppsala you walk in the gardens of Linnaeus, follow in the footsteps of Nobel laureates, and at the same time meet today’s and tomorrow’s smartest teachers and researchers.”

  • United States

    Colorado School of Mines

    Colorado School of Mines (CSM) er et offentlig universitet kjent verden over for sin gode ingeniørutdannelse.