Applied mathematics  is the branch of mathematics focused on developing mathematical methods and applying them to solve real-world problems in science, engineering, industry and technology. Computational mathematics utilises computational techniques and simulations to produce problem-solving techniques and methodologies. This programme is aimed at students who wish to gain a deep understanding of the concepts of modern applied mathematics, and a mastery of the associated mathematical and computational skills. Our students will become autonomous learners capable of formulating and creatively solving relevant problems through techniques in mathematical and computational modeling. Our students will become flexible enough in their thinking and training to apply these techniques to a wide range of fields in the traditional application areas in the Physical Sciences, but also in emerging application areas, such as finance and biology. Our graduates will be in demand by employers and academic research institutes for their ability to use the tools they have learned to explain, describe and predict. We value students who are motivated to find the underlying physical causes for observations and patterns. We aim to provide a teaching and learning environment that develops confidence and independence through a wide variety of interactive formats, both inside and outside the classroom, including lectures, tutorials, on-line course material and computer assisted labs.

1 - Demonstrate an in-depth understanding of core mathematics and a solid knowledge of both abstract mathematics and statistics
2 - Demonstrate strong proficiency in mathematical and computational methods, including computer programming
3 - Apply the tools of mathematical and computational methods, including computer programming, to at least one application area which the students will have studied in depth
4 - Model real-world problems in a mathematical framework, at the same time demonstrating a real understanding of the limitations of modeling and the restrictions imposed by modeling assumptions
5 - Use the language of logic to reason correctly and make deductions
6 - Approach problems in an analytical, precise and rigorous way
7 - Analyze and interpret data and model predictions, find patterns and draw conclusions
8 - Work independently and as part of a team
9 - Carry out research into a specific topic, including a survey and synthesis of the known literature
10 - Give oral presentations of technical mathematical material at a level appropriate for the audience
11 - Prepare a written report on technical mathematical content in clear and precise language

SStudents who return failing grades in a trimester amounting to 15 credits, or more, will be identified under the UCD Continuation – Academic Progress policy. Students whose rate of progression and performance over two academic years is deemed unacceptable will be referred to the Governing Board to be reviewed for exclusion from the programme.

Students who fail to progress from the stage of the programme they are registered to for more than two academic years (except where a period of Leave of Absence has been granted for one of those years) will also be contacted under the Continuation – Academic Progress Policy.

As Stages 3 and 4 have the most dynamic components of the programme, and the material studied previously may no longer be relevant, a student who has been away from the programme for a significant period should be required to register again to Stage 3. The upper limit for completion of Stages 3 and 4 should be six years if they choose to do 120 credits with 20 in each year.

Graduates with training in Applied & Computational Mathematics work in fields as diverse as analytics and forecasting, meteorology, energy systems, electronics, biomedical applications and bio-information, finance, pharmaceutical industry, environmental agencies and companies, and computing in business, technology, research, and academia.

Students take 6 core modules and 20 credits of option modules. Additional modules can be selected from the list of option modules below. Students can also select 10 credits from elective modules.
If you are interested in doing an Internship as part of Stage 4, you must indicate your interest now (in Stage 3). See full details www.ucd.ie/science/careers/internships/students/

Students take 2 core modules and 9 option modules.

Module ID	Module Title	Trimester	Credits
Stage 3 Core Modules
ACM30130	Advanced Computational Science	Autumn	5
ACM30190	Dynamical Systems	Autumn	5
ACM30220	Partial Differential Equations	Autumn	5
ACM30020	Advanced Mathematical Methods	Spring	5
ACM30140	Numerical Methods for PDEs	Spring	5
MATH30040	Complex Analysis	Spring	5
Stage 3 Core Modules
Stage 3 Options - A)MIN0OF: If not previously taken in Stage 2, students must take MATH20310, MATH20300, and STAT20100 in Stage 3.
MATH20300	Linear Algebra 2 for the Mathematical Sciences	Autumn	5
MATH20310	Groups, Rings and Fields	Spring	5
STAT20100	Inferential Statistics	Spring	5
Stage 3 Options - A)MIN0OF: If not previously taken in Stage 2, students must take MATH20310, MATH20300, and STAT20100 in Stage 3.
Stage 3 Options - B)MIN0OF: Students must select a minimum of 20 credits of options in Stage 3. If not previously taken in Stage 2 these options may need to include MATH20310, MATH20300, or STAT20100. Otherwise, all Stage 3 option modules must be taken from the list below.
MATH30090	Metric Spaces	Autumn	5
PHYC30020	Classical Mechanics and Relativity	Autumn	5
STAT20230	Modern Regression Analysis	Autumn	5
STAT30090	Models - Stochastic Models	Autumn	5
ACM30090	Mathematical Biology	Spring	5
ACM30110	Advanced Computational Finance	Spring	10
ACM30200	Mathematical Fluid Dynamics I	Spring	5
ACM30210	Foundations of Quantum Theory	Spring	5
MATH30180	An Intro to Coding Theory	Spring	5
Stage 3 Options - B)MIN0OF: Students must select a minimum of 20 credits of options in Stage 3. If not previously taken in Stage 2 these options may need to include MATH20310, MATH20300, or STAT20100. Otherwise, all Stage 3 option modules must be taken from the list below.
Stage 4 Core Modules
ACM40980	Research Project	2 Trimester duration (Aut-Spr)	10
ACM40690	Survey of Appl and Comp Math	Autumn	5
Stage 4 Core Modules
Stage 4 Options - B)MIN9OF: Students should select at least 9 modules from the list below. Please note that students who successfully completed SCI30080 will be registered by the School to the module. Additional options may be selected, subject to the approval by the program director of ACM and depending on timetable and availability of places. Students take MATH30340 subject to resourcing and approval of module coordinator.
ACM40010	Electrodynamics & Gauge Theory	Autumn	5
ACM40070	Math Fluid Dynamics II	Autumn	5
ACM40750	Gen Relativity & Black Holes	Autumn	5
ACM41020	Maths of Machine Learning	Autumn	5
MATH30340	Peer-Assisted Tutoring	Autumn	5
MATH30360	Measure Theory and Integration	Autumn	5
MATH40830	Maths of Quantum Computation	Autumn	5
SCI30080	Professional Placement-Science	Autumn	5
STAT30010	Time Series	Autumn	5
ACM40900	Weather & Clim Num Modelling	Spring	5
ACM41010	Math of Sust & Environment	Spring	5
ACM41030	Optimization Algorithms	Spring	5
ACM41040	GR and Gravitational Waves	Spring	5
MATH30180	An Intro to Coding Theory	Spring	5
MATH30370	Markov Chains	Spring	5
MATH40480	Probability Theory	Spring	5
STAT40150	Multivariate Analysis	Spring	5
Stage 4 Options - B)MIN9OF: Students should select at least 9 modules from the list below. Please note that students who successfully completed SCI30080 will be registered by the School to the module. Additional options may be selected, subject to the approval by the program director of ACM and depending on timetable and availability of places. Students take MATH30340 subject to resourcing and approval of module coordinator.

		Award		GPA
Programme	Module Weightings	Rule Description	Description
BHSCI001	Stage 4 - 70.00% Stage 3 - 30.00%	Standard Honours Award	First Class Honours	3.68	4.20
			Second Class Honours, Grade 1	3.08	3.67
			Second Class Honours, Grade 2	2.48	3.07
			Pass	2.00	2.47