MySchool

Department of Engineering
Dean:	Dr. Ármann Gylfason
Email:	ru@ru.is
Website:	http://www.ru.is/tvd
Teachers	View

MSc in Financial Engineering
Semesters:	4
Years:	2
ETCS:	120
About major	Fjármálaverkfræði er þverfagleg grein sem samþættir fjármálafræði við verkfræðilegar aðferðir, stærðfræðileg líkön, tölfræði, aðgerðagreiningu og hagnýta tölvunarfræði. Nám í fjármálaverkfræði hentar þeim sem hafa áhuga á t.d. áhættustýringu, afleiðuviðskiptum eða fjárstýringu. MSc námið er mótað að kröfum Verkfræðingafélags Íslands um fullnaðarmenntun í verkfræði.
Learning Outcomes	View
Education cycle	2

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	Mandatory course on major		Teaching language
	Optional course on major		Prerequisites for course

Vorönn/Spring 2024

Energy Financial Assessment

SE-833-FA2

ECTS 6

Engineering Optimization

T-423-ENOP

ECTS 6

Sleep

T-424-SLEE

ECTS 6

Decision Analysis for Management

T-603-AKVA

ECTS 6

Internship in Engineering I

T-706-INT1

ECTS 6

Internship in Engineering II

T-706-INT2

ECTS 6

Systems Biology

T-765-SYBI

ECTS 8

Year

1. year

Semester

Spring 2024

Level of course

First cycle - Advanced / Second cycle - Introductory

Type of course

Elective

Prerequisites

T-101-MATL, Programming in Matlab
T-101-STA1, Calculus I
T-201-STA2, Calculus II
T-211-LINA, Linear Algebra
T-301-MATH, Mathematics III

Schedule

No schedule found.

Lecturer

Eliahu August

Content

Without a quantitative framework to describe networks of interacting components, the functioning of cellular networks cannot be resolved. This course provides the foundation to a quantitative approach to molecular biology by means of mechanistic mathematical models. Throughout the course, we will develop an understanding of the biology of important systems and related biological questions, where mathematics can help in providing answers. We will see how to develop a mathematical model that represents relevant biological processes and use mathematical theories and computational methods to obtain predictions from the model. A final step will be to check that those predictions provide an answer to the biological question. The course topics are as follows: - Nonlinear dynamical systems (ODEs), modelling, and simulation - Analysing ODEs: equilibrium points, limit cycles, stability, and bifurcations - Chemical Reaction Network Theory - Transcription Networks and network motives: Feedback, feedforward, and autoregulation - Enzyme Kinetics - Population Dynamics, models of epidemics

Learning outcome - Objectives

On completion of the course, you should be able to: - formulate and numerically solve mathematical models of different biological processes, - use techniques from nonlinear dynamical systems theory to analyse those models, - describe important biological, physiological, and ecological processes and their respective models, - place the course’s approaches within the wider context of, e.g., drug discovery and chancer therapy.

Course assessment

Presentation, project, final exam.

Reading material

No reading material found.

Teaching and learning activities

Taught for 12 weeks. Lectures, exercises, paper presentations, project.

Language of instruction

English

Project Management and Strategic Planning

T-803-VERK

ECTS 8

Derivatives and risk management