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Applied Scientific Computing, 8 ECTS credits.
/Applied Scientific Computing/
For:
COM
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Prel. scheduled
hours:
Rec. self-study hours: 213
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Area of Education: Technology
Subject area: Mathematics
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Advancement level
(G1, G2, A): A
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Aim:
The courses is aimed to give students the introduction to the computational sciences, a new multidisciplinary field which involves mathematical modeling, numerical solution techniques and the use of computers in solving and analyzing complex problems arising in natural sciences
and engineering. The course has two parts, the first part is a series of lectures introducing the scientific areas included into the Master's Programme in Computational Sciences. The aim of this part is to give an overview of the content of the programme and to stress the multidisciplinary character of Computational Sciences. The second part of the course implies carrying out projects in the four different profiles within the Programme. The aim of the course as a whole is to make students familiar with the content of the Programme and different profiles inherent in it. In order to achieve this goal students have to:
- know the definition and composition of computational sciences
- choose the project within a certain profile
- perform the task specifying in the project
- work in the group and represent the results during the seminars
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Prerequisites: (valid for students admitted to programmes within which the course is offered)
Participants are expected to have a major in mathematics, physics, mechanics, or biosciences, including basic courses in mathematics (calculus, linear algebra, vector calculus, complex functions) and at least one course each in numerical methods and a common computer programming language. Experience in the use of computers is also expected.
Note: Admission requirements for non-programme students usually also include admission requirements for the programme and threshhold requirements for progression within the programme, or corresponding.
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Organisation:
The course contains lectures, seminars and project work.
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Course contents:
The first part of the course contains 14 hours of lectures. The second part of the course includes seminars and project work within four profiles:
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Computational Biosciences (responsible: Bengt Persson)
The project in Computational Biosciences deals with
computer-assisted analyses within the fields of bioinformatics,
computational biology and systems biology. For large-scale analyses of
biological sequence data (DNA or protein), computer-assisted methods
are necessary, both for coping with the enormous amounts of data and
for creating new ways to perform the analyses. The methods include
sequence comparisons, pattern analyses, machine-learning techniques,
molecular modelling, network analyses and evolutionary calculations.
The project can either be oriented towards development of new methods
or towards application/adoption of existing methods on relevant
biological/biomedical problems.
- Scientific Computing and Visualization (responsibles: Lars Eldén, Anders Ynnerman)
The projects in Scientific Computing and Visualization deal with the
solution and/or visualization of problems mainly from the other
branches of the Masters program, but they are method-oriented in the
sense that the emphasis is on problem-solving and visualization tools,
algorithms and their implementation on modern high performance
computers. Examples are the solution of stationary and time-dependent
partial differential equations, and large and sparse eigenvalue
problems arising in mechanics and physics. Large-scale computations
also occur in biosciences and other areas related to data mining and
pattern recognition.
- Computational Mechanics (responsible: Anders Klarbring)
The project in Computational Mechanics deals with the modelling
and simulation of a phenomenon in the mechanics of nature or engineering.
Modern applications for CM concern, for instance, tissues and organs in
animals and humans, where fundamental mechanical equations govern the
biomechanical function of tissues and also control the mechanobiological
response to the environmental conditions. These problems naturally leads
to three-dimensional, time-dependent PDE:s that must be solved using
numerical method such as FEM.
- Computational Physics (responsible: Igor Abrikosov)
The project in Computational Physics deals with the simulations
of matter at the atomic and mesoscopic length scales. The simulation
tools are based on the fundamental principles of quantum or classical
mechanics and statistical physics. They are applied to a wide range of
basic and applied problems, including simulations of the growth of
nanomaterials, properties of quantum wires and quantum point contacts,
theoretical materials design, and charge transport in polymeric materials
and carbon nanotubes. The project emphasizes the interdisciplinary
character of the modern Computational Physics, and includes applications
within chemistry, metallurgy, and geophysics.
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Course literature:
To be announced later.
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Examination: |
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Oral presentation of the projects and a written report
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5,5 p
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8 ECTS
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Course language is English.
Department offering the course: IFM.
Director of Studies:
Examiner: Irina Yakymenko
Course Syllabus in Swedish
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