Department of Information Technology

Doctoral courses in Scientific Computing

The doctoral programme in Scientific Computing is based on a core curriculum of courses that are offered regularly. Typically, two of them are offered each semester. In addition to the core curriculum, other courses and seminars are organized to cover special issues and timely material.

The individual curriculum for a doctoral student should contain a selection of the core curriculum and additional courses of particular relevance for his/her research project. Courses of a general interest, such as Research Ethics and Philosophy of Science, could also be included. Finally, it is emphasized that the curriculum should not only contain courses and seminars. Some portion of the curriculum has to be individual reading of relevant literature.

Courses offered in 2018

course start teacher
Finite element methods III, 7.5 hp January Murtazo Nazarov
Numerical functional analysis, 5 hp TBA Stefan Engblom
Numerical linear algebra, 7.5 hp TBA Maya Neytcheva
Parallel programming for scientific computing, 5 hp Fall 2018 Sverker Holmgren

Courses offered in 2017

course start teacher
Approximation theory, 7.5 hp May 23 Elisabeth Larsson, Murtazo Nazarov Olof Runborg
Numerical optimization, 10 hp September 18 Ken Mattsson, Maya Neytcheva, and Prashant Singh
Parallel algorithms for scientific computing, 5 hp October or November Sverker Holmgren and Maya Neytcheva

Courses offered in 2016

course start teacher
Applied Cloud Computing (SeSE), 5 hp Period 3 Andreas Hellander and Salman Toor
Numerical Methods in Stochastic Modelling and Simulations (CIM), 7.5 hp Period 3 Stefan Engblom and Josef Höök
Matrix Computations in Statistics with Applications (SeSE) Period 3 Maya Neytcheva
Numerical methods for ODEs and DAEs, 7.5 hp (recent information and course syllabus) Period 1 Per Lötstedt, Michael Hanke
Research projects in Scientific Computing, 7.5 hp Period 2 Lina von Sydow

(SeSE) In collaboration with Swedish e-Science Education
(CIM) In collaboration with Centre for Interdisciplinary Mathematics

Current core curriculum

course previous instances periodicity (years)
Classical Articles in Numerical Analysis (CA), 7.5 hp 2015 3-4
Mathematical and numerical techniques for Partial Differential Equations (PDE), 10 hp 2014 3-4
Numerical Functional Analysis (NFA), 5 hp 2014 3-4
Numerical Linear Algebra (NLA), 7.5 hp 2014 3-4
Numerical Methods for ODE (ODE), 7.5 hp 2016 3-4
Numerical Optimization (NO), 7.5 hp 2013 3-4
Parallel Algorithms for Scientific Computing (PASC), 5 hp 2013 3-4
Parallel Programming for Scientific Computing (PPSC), 5 hp 2014 3-4
Research Methods in Scientific Computing, (*) continuously
Mathematical and Computational Consulting, (*) continuously

(*) The number of credit points for this course is flexible and depends on how much work the student puts into the course.

Tentative future overview of core courses

2017 2018 2019 2020 2021
PASC NLA CA ODE NO
NO NFA PDE PASC
PPSC

Other courses

course latest year offered teacher
Finite Element Methods III, 7.5 hp 2010 Axel Målqvist
Iterative solution methods for nonlinear problems, 4.5 hp 2003 Maya Neytcheva
Mathematical Models and Numerical Methods for Fluid Mechanics, 6 hp 2015 Mattias Liefvendahl
Numerical Acoustics, 7.5 hp 2012 Ken Mattsson
Numerical Methods for Nonlinear Hyperbolic PDE, 5 hp 2015 Gunilla Kreiss
Perturbation theory and asymptotic expansions, 5 hp 2014 Elisabeth Larsson
Uncertainty Quantification, 5 hp 2015 Per Lötstedt
Advanced statistical computing (CIM), 5 hp 2015 Behrang Mahjani and Carl Nettelblad
Maximizing performance in practical HPC applications (SeSE) 2015 Maya Neytcheva and Carl Nettelblad
Applied Cloud Computing (SeSE), 5 hp 2016 Andreas Hellander and Salman Toor
Numerical Methods in Stochastic Modelling and Simulations (CIM), 7.5 hp 2016 Stefan Engblom and Josef Höök
Matrix Computations in Statistics with Applications (SeSE) 2016 Maya Neytcheva

(SeSE) In collaboration with Swedish e-Science Education
(CIM) In collaboration with Centre for Interdisciplinary Mathematics

Master level courses

course
Analysis of Numerical Methods, 5 hp
Applied Scientific Computing, 5 hp
Finite Element Methods II, 5 hp
Large Datasets for Scientific Applications, 5 hp
Applied Cloud Computing, 10 hp

Summer/Winter schools

school periodicity latest next
Hartree Unknown 2016
Montestigliano Annualish 2014
Rythms and oscillations Unknown 2014
Zürich summer school Biannual 2014
Jyväskylä Annual 2015
Dobbiaco summer school Annual 2015
Gene Golub summer school Annual 2015 Jul 25-Aug 5, 2016
Fluid Dynamics of Sustainability and the Environment Annual 2015 Sep 5-16, 2016
UPMARC Annual 2015
High-Order Finite Element and Isogeometric Methods Annual 2014
Rome-Moscow school of Matrix Methods and Applied Linear Algebra Annual 2014
International Winter School on Big Data 2015
Oberwolfach seminars Few times a year
Franco-German Summer School on Inverse Problems and Imaging in Bremen Sep 18-22, 2017
Data Science in Göttingen Jul 10-21 2017

Other relevant course sites

Updated  2017-09-18 10:59:28 by Emanuel Rubensson.