Overview & Contacts

Modules

Course components  -  2011/12

The modules taught will cover the following strands:

Bio-inspired Computation: Algorithms for computation that have been inspired by observation of biological systems; simulation of complex biological systems.

Embodied Computation: Physical and bio-chemical systems that are examined from a computational perspective.

Complexity and Emergence: understanding the properties of natural systems, and how these properties are related to the underlying structures.

Taken together, these topics cover a broad range of natural systems, examining each from a computational perspective. In addition to the mandatory Neural Computing, Evolutionary Computation and Swarm Intelligence, students must choose 60 credits from the remaining modules options.

Module Title	Term	Short Description
Neural Computing	Autumn	Algorithms inspired by natural neural systems (Mandatory).
Evolutionary Computation	Autumn	Algorithms inspired by natural evolutionary systems (Mandatory).
Swarm Intelligence	Autumn	An introduction to the basic biology, algorithms, and uses of a range of swarm intelligence approaches (Mandatory).
Quantum Computation	Autumn	An introduction to the theory of quantum computation. In it we will learn about the pioneering quantum algorithms that promise a qualitative leap in computation power over conventional computers (Optional).
User Centred Design	Autumn	User Centred Design introduce students the field of Human-Computer Interaction (HCI). This field covers all aspects of people's interactions with digital systems (Optional).
Emergence	Spring	Complex systems that exhibit emergent properties that cannot be reduced to behaviour of their individual components (Optional).
Complex Dynamical Biosystems	Spring	Complex systems perspective of biosystems and the importance of the powerful central concepts of self-organisation and emergence (Optional).
Computing with Biology and Chemistry	Spring	Theory and practical knowledge in computational systems inspired by biological and chemical systems (Optional).
Quantitative Research Methods	Spring	An introduction to experimental design and statistics as used in HCI and computer science for the evaluation of interactive systems (Optional).
Quantum Information Processing	Spring	An introduction to the theory of quantum information and quantum communication (Optional).
Adaptive & Learning Agents	Spring	This module is situated at the intersection between Machine Learning and Agents. The module covers background in both areas followed by a discussion on the methodology of the emerging AI domain of Adaptive and Learning Agents, and a demonstration of its ideas on a few focus topics (Optional).
Final Project - Natural Computation	Summer	A substantial, independent research project building on the taught course. The deliverable is a dissertation.

Personal Tutor

Each student is assigned to a tutorial group usually containing no more than four or five students, and hence to a personal tutor who will monitor progression.

Assessment

Assessment of students' performance in the course modules will take place in a variety of forms: practical exercises, reports, closed examinations, open assessments and a dissertation for the project. Students are deliberately exposed to a variety of assessment methods so that they are not disadvantaged by background.

Assessments will take place at various times during the year. Practical exercises, reports and other forms of open assessment will be due either during the course module or just after its completion.

Timescales, Modules and Project Descriptions may be subject to change.

Project

Overview

The dissertation project undertaken by students over the summer is carried out individually, which might involve collaboration with another organisation. A collaborative project is still supervised by a member of the Department.

Projects are worth 50% of the total mark for the MSc.

How to Apply

Suitability and Entry Requirements

Typically, you will have achieved at least an upper second class honours degree (or international equivalent) in Computer Science or a related discipline with an appropriate mathematical basis.

We are willing to consider applications from those who do not fit this profile.  We will, for example, consider applicants who do not have an appropriate qualification but have appropriate industrial experience.

How to Apply

For more information about completing your application, please take a look at the University’s webpages which tell you how to apply. 

In particular, please take note of the supporting documents we need to see in order to be able to make a decision about your application.  You are also required to nominate two referees, of which at least one should be from your current employer or place of study.

When you are ready to apply, you can submit your application using our Online Postgraduate Applications Service (OPAS).

While there is no official closing date for applications, it is important to apply as early as possible.

International Students

This course, like all others in the University, welcomes students of all backgrounds and circumstances. 

If English is not your first language, or your first degree was not taught in English, then you will need to have attained a suitable language qualification no more than two years before the start of the course. 

The University's Postgraduate Study webpages will tell you more about the English language requirements for graduate students.

Studentships

The University of York awards a number of scholarships for overseas students each year, and competition for these scholarships is very intense.

Most scholarships only provide partial payment of tuition fees and not living expenses, and most students will need to fund themselves. 

We can give further advice on how much you should budget for and other ways in which you can fund your MSc course; for example career development loans, an employer's bursary or secondment.

Information for students

Being prepared for your MSc in Natural Computation

If you would like to do some reading to prepare, we have selected some books which are used in the first term:

• Williams, C.P. and Clearwater, S.H. (2000) Ultimate Zero and One: Computing at the Quantum Frontier.
  Springer
• de Castro, L.N. and Timmis, J. (2002) Artificial Immune Systems: An Introduction. Springer
• Mitchell, M. (1998) An Introduction to Genetic Algorithms. MIT Press
• Callan, R. (1998) The Essence of Neural Networks. Prentice Hall
• Strogatz, S.H. (1994) Nonlinear Dynamics and Chaos. Westview Press
  

Residency requirements  -  2012/13

Due to the intensive nature of the course, students are required to be in York during the following periods:

• 8 October 2012 - 14 December 2012
• 7 January 2013 - 29 March 2013
• 22 April 2013 - 20 September 2013

However, it should be noted that the MSc is full time and it is assumed that students are working whether or not they are in full attendance.