Exact Sciences Master Guide2005/2006



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naam

Project Software Engineering

code

400067

studiepunten

8

periode

5 en 6

docent

dr. P. Lago

inhoud

Het doel van het SE project is de theorie opgedaan in het SE college toe te passen in een zo¿n realistisch mogelijke praktijksituatie. Het project bestaat uit het construeren van een groot programma in teamverband volgens de RAD (Rapid Application Development) methode. Zoveel mogelijk aspecten van projectmatig werken en software engineering zullen hierbij aan de orde komen, waaronder het opstellen van een projectplan, requirements engineering, design, implementatie en testen, maar ook het samenwerken in een team.

werkwijze

Het uitvoeren van een project in teamverband (4 à 5 personen) met een 'progress report' presentatie van 15 minuten.

literatuur

H. van Vliet, Software Engineering, Principles and Practice, 2nd edition, John Wiley, 2000; Martin Fowler, UML Distilled, 3rd edition, Addison Wesley, 2003.

toetsing

Een team wordt beoordeeld op samenwerking (10%), kwaliteit van de documentatie (25%), kwaliteit van de opgeleverde producten (25%), de consistentie van de documentatie en het eindproduct (10%), projectpresentatie (10%) en een individuele evaluatie (20%).

doelgroep

2I, 2BI, 2MMC, 2BWI, 3AI

voorkennis

Vereiste voorkennis: Practicum Datastructuren (400140).

opmerkingen

Tijdens de eerste drie weken van dit practicum (week 14 t/m 16), wordt er 2 uur college gegeven




subject

Protein Spectroscopy

code

435608

lecturer

dr. G. van der Zwan (contact)

credits

6

period

Not scheduled, can be taken by self-study under the supervision of the lecturer.

aim

Getting acquainted with the principles, techniques and methods, used to study the physico-chemical properties and to characterize proteins.

content

The topics discussed comprise the basic principles of fluorescence spectroscopy, time-resolved fluorescence and fluorescence resonance energy transfer are discussed, this to study the dynamics and kinetics of protein-folding mechanisms.

form of tuition

Lectures and tutorials.

literature

Recent summarizing articles provided by the lecturer.

mode of assessment

Written or oral examination.

entry requirements

Basic knowledge of spectroscopic techniques.

target audience

mCh




subject

Protocol Validation

code

400117

credits

6

period

5 and 6

lecturer

prof.dr. W.J. Fokkink

aim

Learning to use formal techniques for specification and validation of communication protocols.

content

This course is concerned with specification and validation of protocols, using formal methods. The course is based on a specification language based on process algebra combined with abstract data types, called mCRL. This language and its toolset can be used for specification of parallel, communicating processes with data. Model checking is a method for expressing properties of concurrent finite-state systems, which can be checked automatically. Interesting properties of a specification are: "something bad will never happen" (safety), and "something good will eventually happen" (liveness). In the lab we will teach the use of a tool for automated verification of the required properties of a specification.

form of tuition

Lectures with practical work. During the labs the mCRL-tool and a model checker will be used for validation of protocols discussed during lectures.

literature

Lecture notes: Modelling Distributed Systems, written by J.F. Groote, W. Fokkink and M. Reniers.

mode of assessment

Written exam, together with a homework assignment. The overall mark of the course is (H+4W)/5, where H is the mark for the homework assignment, and W is the mark for the written exam.

entry requirements

Inleiding Logica (400119), Datastructuren (400145)

target audience

3I, 3BI, 3AI, mCS, mPDCS

remarks

Once every other year, not in spring 2007.




subject

Putting Electrons to Work: the Science behind Modern Devices

code

420060

lecturers

dr. T. Gregorkiewicz (UvA); dr. E.H. Brück (UvA, phone: +31 (0)20 5255640, e-mail: bruck@science.uva.nl)

credits

6

period

5

aim

Discussion of the subtle physics behind modern electronic and magnetic devices.

content

  • Electrons in semiconductors & metals: Doping: effective mass approximation, Spin scattering & Magneto-resistance.

  • Low dimensional structures: Quantum dots and wires, 2-D structures, Magnetic multilayers, Spin-valves.

  • Optical properties: Optical doping, Dynamical aspects, Magneto-optics.

  • Experimental techniques: Photoluminescence, Absorption, Raman spectroscopy, Magneto-optics and magnetic resonance, Magnetization, Magneto-transport.

  • Devices: Diodes and transistors, LED's, Semiconductor lasers, Magnetic disks, MO storage, MRAM, GMR sensors, Spin-polarized FET.

form of tuition

Interactive course.

literature

S. Elliott: The Physics and Chemistry of Solids; F.G. Smith and T.A. King: Optics and Photonics: an Introduction Physics Today, Special Issue Magneto Electronics, April 1995 48(4), 1995

mode of assessment

Excercises, examination and presentation.

target audience

mPhys, mCh

remarks

Registration via http://studieweb.student.uva.nl three weeks prior to the start of the course. Course registration includes registration for the examination. Registration is also possible at the Education Office, phone: +31 (0)20 5257100, e-mail: ondwns@science.uva.nl. For the course schedules consult the separate schedule guide or see http://www.student.uva.nl/ or contact the dr. Brück.




subject

Qualitative Research Methods for the Information Sciences

code

400290

credits

3

period

3

lecturers

prof.dr. J.M. Akkermans (contact); dr.ing. J. Gordijn

aim

This course helps prepare students who want to embark on their (Master) research.

content

The course provides an overview and assessment of different scientific research methods,

needed in a multi-disciplinary approach to Information Systems and how

they function in an organizational context. Major topics are:

- developing the research questions you want to answer;

- planning your research;

- qualitative research methods (e.g. interview, case study, action research, ethnography);

- quantitative research methods (e.g. survey, questionnaire, statistical data analysis);

- IS research methods (e.g. modelling, prototyping, simulation, scenario analysis);

- aspects of theory formation;

- how do you (and others) know that your research results are valid?;



- research report writing.

form of tuition

In group sessions, we will critically review existing samples of research (papers, articles, MSc theses) against criteria of scientific argumentation, validity, soundness, completeness.

literature

Reader with recent articles, plus textbook: Pervez Ghauro and Kjell Gronhaug, Research Methods in Business Studies, 2nd ed, Prentice Hall, Essex UK, 2002

mode of assessment

Classroom presentation and written review essay

entry requirements

Bachelor-level IK, IN or AI

target audience

mIS, mCS, mAI

remarks

A useful reference point is the document that specifies the procedure and criteria for Master research (see study guide).




subject

Quantum Stochastics

code

400248

lecturer

prof.dr. R.D. Gill

credits

6

period

4, 5 and 6

aim

Quantum mechanics is a stochastic theory: it makes stochastic predictions about the outcomes of measurement or other kinds of interaction with a quantum system. If the state of the quantum system being measured is not known, or depends on some unknown parameters, we have a classical statistical model on our hands. It turns out that the amount of information which can be got from measuring the system is bounded. Moreover, getting a lot of information about one parameter makes it harder to learn about another. The mathematical framework to describe these problems turns out to be surprisingly elegant and simple. Some basic linear algebra, some elementary trigonometry and elementary probability, and the most basic facts about complex numbers, allow us to describe some quantum statistical problems which are of burning interest to experimenters and theoreticians working in the field of quantum information today.

form of tuition

Lectures.

literature

We will be using the "bible of quantum information", a book by Nielsen and Chuang, further details on the course home pages http://www.math.vu.nl/sto/onderwijs/sfm/prog.html
Participants will need to get themselves a copy, as soon as possible.

mode of assessment

Will be announced.

entry requirements

No physics background is needed for this course (in fact, it might even be a disadvantage!).

target audience

mMath

remarks

Registration: via http://studieweb.student.uva.nl
Course: three weeks prior to the start of the course.
Examination: one week prior to the examination date.
Registration is also possible at the Education Office, phone: 525 7100, e-mail:  ondwns@science.uva.nl




subject

Queueing Theory

code

400397

lecturer

W.R.W. Scheinhardt

credits

6

period

4 and 5

content

The following subjects will be treated:

   * Basic concepts (modeling, Little's formula, PASTA property, Laplace-Stieltjes transform, probability generating function)


    * Birth-death-type queues (M/M/1 queue, M/M/1/K queue, M/E_r/1 queue)
    * M/G/1 queue
    * Priority queues
    * Insensitive queues (M/G/C/C/ queue, M/G/1/PS queue)

literature

 Lecture notes of the course "Queueing Theory", Department of Mathematics and Computer Science, Eindhoven University of Technology. In addtion (also to indicate the level):

    * Nelson, Probability, stochastic processes and queueing theory, Springer, 1995


    * W. Wolff, Stochastic modeling and the theory of queues, Prentice-Hall, 1989

mode of assessment

Take home problems.

entry requirements

Basic knowledge of probability theory at the level:
S.M. Ross, Introduction to probability models, 8th edition, Academic Press, 2003 (chapters 1-3).

target audience

mMath

remarks

12 Mondays 10.15 - 12.00 (January 24 - March 21 & April 4 - April 18) at the University of Utrecht
As this course is part of the joint national master programme registration via http://mastermath.nl 




subject

Rational Points on Curves

code

400403

credits

8

period

4, 5 and 6

target audience

mMath

remarks

  • As this course is part of the joint national master programme registration via http://mastermath.nl 

  • Location Utrecht




subject

Reaction Dynamics in Condensed Phase and Bio-Systems

code

435652

lecturer

dr. G. van der Zwan

credits

6

period

Not scheduled, can be taken by self-study under the supervision of the lecturer.

aim

The course provides insight in the effects of solvents and solvent dynamics on elementary processes taking place in it.

content

Electron transfer (Markus theory) and proton transfer (tunneling vs barrier processes) in the condensed phase. Non-equilibrium free energy, dielectric relaxation and solvent dynamics. Solvent effects in time-resolved spectroscopy. Excited state proton transfer reactions in chemical and biophysical systems.

form of tuition

Lectures 18 hours, tutorials 18 hours.

literature

Lecture notes.

mode of assessment

Written examination.

target audience

mCh




subject

Receptor Structure and Function

code

435680

co-ordinator

dr. M.J. Smit (tel 598 7572; e-mail: smit@few.vu.nl)

lecturers

dr. M.J. Smit; prof.dr. R. Leurs

credits

6

period

4, 5 and 6

aim

To obtain extensive knowledge of the molecular aspects of drug targets and their interaction with ligands.

content

This course comprises a more elaborate study of fundamental principles and aspects of receptor structure and function within the field of Molecular Pharmacology. In depth insight in molecular mechanisms by which most important groups of drugs act will be provided, focusing on ligand-receptor interactions and intracellular signalling pathways activated by these receptors. Modern pharmacological concepts such as e.g. constitutive receptor activity, receptor regulation and dimerization will be addressed.

form of tuition

Lectures, tutorials and self-study.

literature

Textbook Receptor Pharmacology - second edition - edited by J.C. Foreman and T. Johansen (ISBN 0- 8493-1029-6), selected primary (original research papers) and secondary (review papers) literature.

mode of assessment

Written examination.

entry requirements

Course on Pharmacodynamics of Drug Action.

target audience

mPhar

remarks

Please contact the coordinator four weeks prior to the start of the course (e-mail: smit@few.vu.nl).




naam

Rechtzoeken (B2/BN2)

code

200201

studiepunten

2,9

docent

drs. A.J. Wolthuis (kamer 7A-37, tel. (020) 59 86326)

periode

Rechtzoeken wordt tweemaal per jaar gegeven: direct na de zomervakantie en direct na de kerstvakantie. Let goed op de collegeroosters voor de precieze datum van het hoorcollege.

doel

Rechtzoeken is een vaardighedenvak. U schrijft een werkstuk en houdt een toespraak aan de hand van een door de docent op het hoorcollege uit te reiken opdracht. U werkt samen met één andere student. Door een werkstuk te maken en een toespraak te houden, oefent u in het vinden en raadplegen van juridische bronnen, het begrijpen van juridische teksten, het stellen en beantwoorden van een juridische vraag en het schrijven en presenteren van een juridisch betoog. Tenslotte oefent u de vaardigheid samen met een ander binnen een bepaalde termijn een opdracht uit te voeren.

werkwijze

U dient zich samen met een collega-student voor het vak in te schrijven op een lijst die op de balie van het studie-informatiepunt (kamer 5A-13) ligt. Het is verstandig u al vóór de vakantie in te schrijven voor de cursus, die direct na de vakantie van start gaat. U schrijft zich automatisch in voor een presentatiedatum. Schrijf uw naam onder een presentatiedatum die u schikt. Noteer uw inschrijfnummer en de presentatiedatum.
Recht zoeken kent per gelegenheid één hoorcollege waar uitgelegd wordt wat van u wordt verwacht. Op dat hoorcollege worden bovendien de opdrachten uitgedeeld. Als het hoorcollege is verstreken, worden geen opdrachten meer uitgereikt.
Het werkstuk moet twee weken na het uitdelen worden ingeleverd bij het studie-informatiepunt. Wanneer u een onvoldoende voor het werkstuk hebt behaald, komt u niet in aanmerking voor het houden van een presentatie. De docent zendt u in dat geval enkele dagen vóór de presentatiedatum een e-mail met daarin uw cijfer en commentaar op uw werkstuk. Wanneer u het werkstuk voldoende hebt gemaakt, krijgt u pas na uw presentatiedatum een e-mailbericht met daarin uw cijfer en het commentaar.

literatuur

Syllabus Rechtzoeken 2005 (te zijner tijd verkrijgbaar via Blackboard).

toetsing

Werkstuk en presentatie

opmerkingen

Inschrijving
U dient zich samen met een collega-student voor het vak in te schrijven op een lijst die op de balie van het Studie-informatie(punt)(kamer 5A-13) ligt. Het is verstandig u al vóór de vakantie in te schrijven voor de cursus, die direct na de vakantie van start gaat. U schrijft zich automatisch in voor een presentatiedatum. Schrijf uw naam onder een presentatiedatum die u schikt. Noteer uw inschrijfnummer en de presentatiedatum.

voorkennisvak

200109 : Project (B1)




subject

Recursion Theory

code

400239

credits

6

period

1 and 2

lecturer

dr. B. Löwe

content

This lecture course will cover the basics of recursion theory (models of computation, limitative theorems) and discuss the connections between recursion theory and the foundations of mathematics (Gödel's Incompleteness Theorem). After that, recursion-theoretic hierarchies (Turing degrees) will be introduced.

form of tuition

Lecture Course

literature

Barry Cooper, ""Computability Theory"" (Chapters 1-10).

mode of assessment

Weekly homework

entry requirements

Mathematical maturity, some basic knowledge of first-order logic

target audience

mMath

remarks

  • Registration via http://studieweb.student.uva.nl Course: three weeks prior to the start of the course. Examination: one week prior to the examination date. Registration is also possible at the UvA Education Office, phone: (020) 525 7100/7049, e-mail: ondwns@science.uva.nl (mathematics and physics students). For the course schedules please consult the separate UvA schedule guide or phone the Education Office.




subject

Research Methods I for Artificial Intelligence: Data collection (Onderzoeksmethoden 1 voor AI: Dataverzamelingstechnieken)

code

812025

credits

6

period

2

lecturers

dr. C. Bruinsma; dr. J.R.P.B. de Mey; dr. E.A.J. van Hooft (coordinator); drs. L.M. de Wit; dr. F.A. Goossens

aim

After completing this course, students should be able to: i) describe the characteristics, advantages, and disadvantages of the following data collection methods: observation, interviewing, questionnaires, and psychological tests. ii) identify and explain the most important types of reliability and validity. iii) use the various methods of data collection in a specific research context. iv) evaluate the various methods of data collection on their practicality, reliability, and validity for a specific research question.

content

This course concerns research methods related to the translation of a theoretical or diagnostic research question into a workable research design. The course starts with an introductory module on research questions and research designs. The following modules focus on observational methods, interview methods, survey research, psychological testing, reliability and validity, and unobtrusive methods, respectively. The course concludes with a comparison of the methods of data collection.

form of tuition

Lectures

literature

  • Robson, C. (2002). Real world research: A resource for social scientists and practitioner-researchers (2nd edition). Oxford, UK: Blackwell.

  • Urbina, S. (2004). Essentials of psychological testing. Hoboken, NJ: Wiley.

  • Studiehandleiding Onderzoeksmethoden I: Dataverzamelingstechnieken. Amsterdam: Vrije Universiteit.

  • See blackboard and the `Studiehandleiding¿ for a listing of additional literature

mode of assessment

Multiple-choice test

entry requirements

Introduction to Research Methods (Algemene Methodologie)




subject

Research Proposal Writing

code

400364

credits

9

period

1, 2 and 3

target audience

mPDCS




subject

Scheduling

code

400396

lecturer

J. Hurink

credits

6

period

4 and 5

aim

This course gives an introduction into scheduling theory and its application.

content

 The term scheduling represents the assignment of resources over time to perform some tasks, jobs or activities. Feasible schedules are compared with respect to a given optimality criterion. Mostly, the optimization problem is combinatorial and very complex. From a computational point of view these problems are hard (NP-hard) and the classical techniques fail in practice. Therefore, the optimal solution is often approximated by heuristics.
The following subjects are discussed:
-  CPM and PERT
-  Single-machine models (exact and approximation methods)
-  Parallel machines
-  On-line models
Open shop, flow shop and job shop models
-  Timetabling

literature

    *  Pinedo, Michael L: Planning and Scheduling in Manufacturing and Services;
      Series: Springer Series in Operations Research and Financial Engineering, 2005, XVI, 512 p. With CD-ROM., Hardcover, ISBN: 0-387-22198-0
    * Brucker, Peter: Scheduling Algorithms
      4th ed., 2004, XII, 367 p., Hardcover, ISBN: 3-540-20524-1
    * handout for special subjects

mode of assessment

 Take home problems.

entry requirements

 Basic knowledge (bachelor level) of analysis and linear algebra.

target audience

mMath

remarks

12 Mondays 13.00 - 14.45 (January 24 - March 21 & April 4 - April 18) at the University of Utrecht.
As this course is part of the joint national master programme registration via http://mastermath.nl




subject

Science and Technology of Hydrogen in Metal

code

420065

lecturer

prof.dr. R.P. Griessen

credits

6

period

4

aim

Understanding the remarkable physical properties of metal-hydrides and their applications within a future hydrogen energy scenario.

content

This course provides a playground for applications of essentially all concepts in Condensed Matter Physics: electronic band structure, zero-point-motion, anharmonicity, correlation and screening effects in negative H-ion, optical phonons, electron scattering by optical phonons, diffusion (also driven by external fields), phase diagrams, spinodal decomposition, macroscopic density modes, metal-insulator transition, and optical properties (bulk and nanostructured in naturally disproportionated hydrides). Hydrogen storage materials, batteries, and hydrogen operated devices are discussed within the context of a sustainable hydrogen energy scenario.

form of tuition

Selfstudy and a number of contact hours.

literature

The course is based on the new lecture notes "Science and Technology of Hydrogen in Metals" and a number of review papers.

mode of assessment

Oral examination

entry requirements

Condensed matter physics, statistical physics and quantum mechanics (Ba-physics level).

target audience

mPhys.

remarks

Registration for this course via https://tisvu.vu.nl/tis/menu, two weeks prior to the start. This is an optional course for master students condensed matter science.




subject

Scientific Computing

code

400238

credits

6

period

1, 2 and 3

target audience

mMath

remarks

For further information see: www.mastermath.nl




subject

Scientific Visualisation

code

400114

credits

4

period

1 and 2

content

This lecture consists of the first half (about Scientific Visualization) of the lecture "Natuurkundige Informatica 1" (Division of Physics and Astronomy), extended with extra practical assignments for computer science students.

form of tuition

Class with integrated computer practicum.

target audience

mCS, mPDCS




subject

Semiparametrics Statistics

code

400257

credits

8

period

4, 5 and 6

lecturer

prof.dr. C.A.J. Klaassen

aim

Controlling the basic principles of semi parametric statistics

content

Classical Statistics considers models with a (finite dimensional) Euclidean parameter. These parametric models may be extended to so-called semiparametric models by adding infinite-dimensional parameters. One of the most important examples is the extension of the linear regression model with normal errors to the semiparametric regression model in which the errors are just assumed to have mean zero; the shape of the error distribution being the added infinite-dimensional parameter. The goal is asymptotically efficient estimation of the Euclidean regression parameters. The theory that will be discussed, has been developed in the last two decades. It will be illustrated via the above mentioned regression model (applied in e.g. econometrics), the symmetric location model, the Cox proportional hazards model (applied in medical statistics), and other models.

form of tuition

Lectures and practical work

literature

Lecture notes.

mode of assessment

Exercises and an oral examination.

entry requirements

Measure Theoretic Probability, Asymptotic Statistics.

target audience

mMath, mSFM

remarks

  • As this course is part of the joint national master programme registration via http://mastermath.nl 

  • Location VU.




subject

Separation Sciences

code

435609

lecturers

dr. W.T. Kok; dr. H. Lingeman; prof.dr.ir. P.J. Schoenmakers; dr. J.J. Vreuls

credits

6

period

2

aim

Offering insight into modern analytical chemistry.

content

The topics discussed comprise the fundamentals, theory and practice of gas and liquid chromatography, electrophoresis, hyphenated systems and 2-dimensional separation techniques. The course is an extension of the introductory course 'Principles of Analytical Chemistry'.

form of tuition

Lectures and tutorials.

literature

Recent summarizing articles provided by the lecturer and C.F. Poole and S.K. Poole, Chromatography Today.

mode of assessment

Written or oral examination.

entry requirements

Basic knowledge of modern analytical separation and detection systems as discussed in 'The course 'Principles of Analytical Chemistry'.

target audience

mCh

remarks

Registration for this course via https://tisvu.vu.nl/HTM/TISVULogin.htm, one week prior to the start. For the course schedules please refer to http://www.few.vu.nl/onderwijs/roosters.




subject

Sequence Analysis

code

430045

credits

6

period

2

lecturers

dr. J. Kleinjung; prof.dr. J. Heringa

aim

A theoretical and practical bioinformatics course about biological sequence analysis. The course provides an introduction to the algorithmic and biological principles of sequence analysis, as well as practical implications.

Goals:

  • At the end of the course, the student will be aware of the major issues, methodology and available algorithms in sequence analysis.

  • At the end of the course, the student will have hands-on experience in tackling biological problems in sequence analysis.

content

Theory:

  • Dynamic programming, database searching, pairwise and multiple alignment, probabilistic methods, pattern matching, evolutionary models, and phylogeny.

Practical:

  • Assignment programming own alignment software based on dynamic programming

  • Assignment homology searching and pattern recognition using biological and disease examples

  • Assignment multiple alignment of biological sequences

form of tuition

13 Lectures (2 two-hour lectures per week), Assignment introductions, Computer practicals, Hands-on support

literature

  • E-course material: http://ibivu.cs.vu.nl

  • Books: Richard Durbin, Sean R Eddy, Anders Krogh, Graeme Mitchison (1998). Biological Sequence Analysis. Cambridge University Press, 350 pp., ISBN 0521629713.

mode of assessment

Assignment results and oral or written exam (depending on number of course students)

entry requirements

Bachelor Physics, Chemistry, Mathematics, Computer Science, Biology, Medical Natural Sciences. Some experience in programming is required.

target audience

Students with Bachelor Physics, Chemistry, Mathematics, Computer Science, Biology, or Medical Natural Sciences, with a strong interest in Bioinformatics

remarks

The course is taught in English




subject

Simulation Methods in Statistics

code

400258

credits

6

period

1 and 2

lecturer

dr. A.J. van Es

content

Nowadays simulation methods based on random number generation on powerful computers play an important role in statistics. We highlight two methodologies, the bootstrap and Monte Carlo Markov chain simulation. The bootstrap method has been introduced in 1977 by Efron. This is a useful, generally applicable, but computationally intensive, method to construct, for instance, confidence intervals. The basic idea of the method is resampling from the original data. The naive bootstrap, paramatric bootstrap and smooth bootstrap shall be discussed. By running a computer simulated Markov chain for a suitably long time we can generate observations from a distribution close to the stationary distribution of the Markov chain. By choosing suitable transition probabilities practically any distribution can be simulated in this way. We will discuss the Gibbs and Metropolis algorithms, the basic algorithms for this kind of simulation, as well some of their refinements, bearing in mind the relevance for statistics.

form of tuition

Lectures and exercises

literature

Lecture notes

mode of assessment

Exercises and oral examination.

entry requirements

knowledge of basic statistics, measure theoretic probability

target audience

mMath, mSFM

remarks

  • Registration via http://studieweb.student.uva.nl. Course: three weeks prior to the start of the course. Examination: one week prior to the examination date. Registration is also possible at the UvA Education Office, phone: (020) 525 7100/7049, e-mail: ondwns@science.uva.nl (mathematics and physics students). For the course schedules please consult the separate UvA schedule guide or phone the Education Office.




subject

Software Architecture

code

400170

credits

6

period

2 and 3

lecturers

prof.dr. J.C. van Vliet; dr. P. Lago

aim

Get acquainted with the field of software and information architecture. Understand the drivers behind architectural decisions. Be able to develop and reason about an architecture of a non-trivial system.

content

Students work in groups to develop an architecture for a fictitious system. They have to develop different representations (called views) of the architecture. These different representations emphasize different concerns of people that have a stake in the system. Each group will also be asked to assess ("test") the architecture of another group for certain quality attributes.

form of tuition

Group work with a number of assignments

literature

Len Bass et al, Software Architecture in Practice (second edition), Addison-Wesley, 2003

mode of assessment

Written reports of the assignments, presentation, exam

entry requirements

Sofware Engineering.

target audience

mCS, mIS

remarks

Students are required to sign up for this course at Blackboard.




subject

Software Configuration Management

code

400413

lecturer

dr. R.L. Krikhaar

credits

6

aim

The goal of the course is to learn the basic concepts and principles of Software Configuration Management and to learn how to select and apply them in a real-world context.

content

Software Configuration Management (SCM) is required to control evolving software systems.
This course introduces the basic concepts and principles underlying software configuration management, a.o. change control, version management, build management and release management.
Tools are inevitable for SCM, therefore a number of SCM tools are compared to the discussed concepts and one or two of them are practiced.
New research areas of SCM are discussed: multi-disciplined configuration management, multi-sites CM and CM for multiple products (product families).
In addition, the lectures will also cover SCM experiences in industry.

form of tuition

- Lectures
- Working Lectures (article reviews)
- Practice (workshop with a commercial SCM tool)

literature

- SCM book (to be announced before course starts)
- Articles (to be selected during course)

mode of assessment

- Review of articles (presentation)
- SCM study in industry (paper)

entry requirements

Bachelor Informatica, especially
 - 400071 Software Engineering
 - 400067 Project Software Engineering

target audience

mCS




subject

Spectroscopy, Astrophysics and the Earth's Atmosphere

code

420090

lecturers

prof.dr. W.M.G. Ubachs; dr. H. Linnartz; prof.dr. I. Aben

credits

6

period

5

content

The energy-level structure of molecules will be analyzed starting from the Schroedinger equation and the Born-Oppenheimer approximation: electronic structure, vibrational structure and rotational structure; fine structure effects in open shell molecules, spin-orbit splitting, Lambda-doubling. Spectra of molecules will be treated in the uv-visible, infrared and far-infrared. Rotations and vibrations of polyatomic molecules, and tunneling phenomena. Detection of molecules in outer space (interstellar medium, comets) and the Earth's atmosphere, including retrieval methods for determining column densities in the earth's atmosphere from satellite data; radiative transfer in the atmosphere.

mode of assessment

Practical tasks and oral examination.

target audience

mPhys, mCh

remarks

Registration for this course via https://tisvu.vu.nl/tis/menu, two weeks prior to the start. Is obligatory; particpation is not allowed without prior registration !




subject

Statistical Data Analysis

code

420067

lecturers

dr. E. de Wolf (UvA, phone: +31 (0)20 5925123, e-mail: edewolf@science.uva.nl); dr. T.J. Ketel

credits

6

period

1 and 2

aim

The purpose of the course is to present the basic mathematical and computational tools needed for the statistical analysis of experimental data. The methods will be practiced by writing and running short computer programs.

content

Main topics:

  • Probability: definition and interpretation, Bayes theorem. 

  • Distributions of random variables: random variables, probability density functions, expectation values, (co)variances, normalized distribution, Chebychev-inequality, transformation of variables, matrix-formalism, error propagation.

  • Examples of probability functions: binomial, multinomial, Poisson, uniform, exponential, Gaussian, chi-square, Cauchy; the law of large numbers, the central limit theorem.

  • The Monte Carlo method: generators for the uniform distribution; methods for non-uniform distributions.

  • Parameter estimation (general concepts): samples, properties of good estimators; estimators for mean and variance.

  • The method of maximum likelihood: the likelihood function, ML estimators for parameters of Gaussian and exponential distributions; variance of ML estimators, the information inequality; extended ML, ML with binned data; analytical and numerical methods.

  • The method of least square (LS): relation to ML, linear and non-linear LS-fit, LS with binned data, combining measurements with LS; analytical and numerical methods.

  • Testing the goodness-of-fit: the chi-squared distribution, degrees of freedom.

  • Least squares fitting with constraints: method of Lagrange multipliers.

form of tuition

Lectures and exercises.

literature

Course notes. S. Brandt, G. Gowan: Data Analysis, Statistical and Computational Methods for Scientists and Engineers, Springer Verlag, 1998.

mode of assessment

Will be announced.

target audience

mPhys.

remarks

Registration via http://studieweb.student.uva.nl three weeks prior to the start of the course. Course registration includes registration for the examination. Registration is also possible at the Education Office, phone: +31 (0)20 5257100, e-mail: ondwns@science.uva.nl. For the course schedules consult the separate schedule guide or see http://www.student.uva.nl/




subject

Statistical Genetics

code

400296

credits

6

lecturer

prof.dr. A.W. van der Vaart

period

This course will not be given this year. Students interested in a reading course on this subject can contact professor van de Vaart.

content

Probability and statistics play an important role in genetics. The mechanism of "meiosis", the forming of sperm or egg cells, is thought to be probabilistic in nature, as is the process of mating in large populations. The relationship between "genotypes" (DNA-sequence) and "phenotypes" (observable traits or diseases) can be modelled by probability distributions. The analysis of genetic determinants is based on random samples from a population, often biased, and various statistical methods are necessary to analyse such data. This course provides an introduction to stochastic models and methods used in genetics, directed at students in mathematics. We do assume a good working knowledge of probability and statistics (e.g. likelihood and Bayes inference, asymptotics, testing), but do not assume prior knowledge of genetics. In particular, the jargon in this description will be explained.

Statistical genetics is a classical branch of applied probability and statistics, which has recently gained much new interest, due to the signicifant breakthroughs in genetics, both experimentally and theoretically. With modern techniques and significantly increased data it is hoped to link diseases and other traits to genes (pieces of DNA) that can be precisely located on the genome in an unprecedented manner. This course incorporates parts of many different areas of statistics.

Of course we start with Mendel¿s laws of "segregation", which stipulate that each parent passes a randomly chosen gene on to his/her offspring from each pair of genes, independently across genes. The latter independence was later found out to be untrue, and replaced by "linkage models", which stipulate positive dependence between genes sitting close together on the genome. The most popular model is based on a Poisson process model for "crossovers" during meiosis. The resulting models combined with "penetrance models" (conditional distributions for phenotypes given genotopyes) allow to write likelihoods for the observed phenotypes in families (or "pedigrees"), and thus to estimate the dependence of phenotypic traits on genetic factors. Because a full likelihood analysis requires the specification of many probability densities and is computationally intensive, other methods with the same aim are based on reduced data, in particular "IBD" (identity by descent) status. "Association" studies are based on the idea that, under a random mating assumption, a population should tend to equilibrium, with deviations in pairs of genes (possibly)in a random sample of individuals indicating that these genes are close together on the genome. Finally, "biometric analysis" is directed at decomposing phenotypic variation into genetic and environmental parts.


literature

Lecture Notes.

Pak Sham: Statistics in Human Genetics.

Kenneth Lange: Mathematical and Statistical Methods for Genetic Analysis.

Elizabeth Thompson: Statistical Inference from Genetic Data on Pedigrees.



entry requirements

At least two courses in probability and two courses in statistics + general mathematical training.

target audience

mMath

remarks

http://www.math.vu.nl/sto/onderwijs/statisticalgenetics/




subject

Statistical Models

code

400171

credits

4

period

1 and 2

lecturer

dr.ir. G. Jongbloed

aim

Introduction to several frequently used statistical models and their application.

content

Analysis of variance, generalized linear models, non-linear models, time series.

form of tuition

Course of lectures as well as data analysis exercises with the computer (R).

literature

Lecture notes.

mode of assessment

Written exam plus exercises.

entry requirements

Prerequisite: Algemene Statistiek (400004), Statistische Data Analyse (400073). Prerequisite for participation in written exam: sufficient mark for the exercises.

target audience

mMath, mBMI, mEctrie




subject

Statistical Physics and Condensed Matter Theory I

code

420083

lecturer

prof.dr. B. Nienhuis (UvA, phone: +31 (0)20 5255749, e-mail: nienhuis@science.uva.nl)

credits

6

period

1 and 2, 6 cp and optional in period 3, 2 cp.

content

Various subjects in statistical physics and theoretical condensed matter physics will be treated; the precise content of the course will be announced on the website http://www.science.uva.nl/~nienhuis/SPCMT1

form of tuition

Lectures and exercises.

literature

To be announced on the website.

mode of assessment

Examination in consultation with the students.

target audience

mPhys.

remarks

Registration via http://studieweb.student.uva.nl three weeks prior to the start of the course. Course registration includes registration for the examination. Registration is also possible at the Education Office, phone: +31 (0)20 5257100, e-mail: ondwns@science.uva.nl. For the course schedules consult the separate schedule guide or see http://www.student.uva.nl/




subject

Statistical Physics and Condensed Matter Theory II

code

420100

lecturer

prof.dr. A.M.M. Pruisken (UvA, phone: +31 (0)20 5255746, e-mail: pruisken@science.uva.nl)

credits

6

period

4 and 5

content

In this course we study the effects of interactions and disorder on the behaviour of electrons. In the first part we introduce general concepts like Fermi liquid theory, spin and charge ordering, the metal-insulator transition, superconductivity, the Kondo effect, Anderson localization, the quantum Hall effect etc. The second and main part of this course deals with the Renormalization Group, the fermionic path integral and their applications to the correlated electron gas.

form of tuition

Lectures and exercises.

literature

Will be announced.

mode of assessment

In consultation with the students written or oral examination.

target audience

mPhys.

remarks

Registration via http://studieweb.student.uva.nl three weeks prior to the start of the course. Course registration includes registration for the examination. Registration is also possible at the Education Office, phone: +31 (0)20 5257100, e-mail: ondwns@science.uva.nl. For the course schedules consult the separate schedule guide or see http://www.student.uva.nl/




subject

Statistics and Chemometrics

code

435624

lecturers

dr. W.T. Kok; dr. J.A. Westerhuis

credits

6

period

3

aim

Provide the student with statistical knowledge necessary in analytical chemistry.

content

Since analytical chemistry is mainly about measurements and results. However none of these results tell us the truth. Statistics is used to draw conclusions from the results. This course discusses t-tests to compare means, F-tests to compare standard deviations, experimental design, robustness tests, Analysis of Variance and calibration lines. Furthermore, chemometrics will be introduced and the main chemometric methods (principal component analysis, principal component regression) will be covered.

form of tuition

lectures and tutorials

literature

J.N. Miller and J.C. Miller: Statistics and Chemometrics for Analytical Chemistry.

mode of assessment

Written examination

entry requirements

Course 'Principles of Analytical Chemistry'.

target audience

mCh

remarks

  • Course: at the latest three weeks prior to the start of the course via the UvA 'studieweb': http://studieweb.student.uva.nl (`werkgroepen')
    Examination: at the latest one week prior to the date of the examination via studieweb (`tentamen'). Registration is also possible at the Education Office.

  • contact: dr. J.A. Westerhuis, Tel. 525 6546, westerhu@science.uva.nl.

    For more schedule information please consult the UvA schedules or the Education Office, Tel. 525 7049, svhouten@science.uva.nl.






subject

Statistics and Probability Seminar

code

400135

credits

4

lecturers

dr. M.C.M. de Gunst; dr.ir. G. Jongbloed; prof.dr. R.W.J. Meester; prof.dr. A.W. van der Vaart

period

not fixed

content

The subject will be chosen in consultation with the students. Possibilities include bootstrap methods, statistics for point processes, survival analysis, statistics for genetics, hidden Markov models, Markov chain Monte Carlo methods.

form of tuition

Participants will present chapters from books or articles. The style will be informal. Presentation and global understanding will be the main focus. This seminar is meant specifically for students; one or more docents will guide the seminar.

mode of assessment

None.

entry requirements

General Statistics (400004). Interested students are requested to contact one of the docents ample time before they wish to start.

target audience

3W, mMath

remarks

Registration for this course is compulsory via https://tisvu.vu.nl/tis/menu, two weeks prior to the start.


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