Key Info

Bachelor of Science in Mathematical Sciences

NFQ Level 8 major Award Honours Bachelor Degree

Entry route(s):

Course code
LM124
Duration
4 Years
Subject area
Science
Course Director
Norma Bargary
Email
norma.bargary@ul.ie
Tel
061 234759
Admissions:
Tel
+353 (0)61 233755

If you like mathematics and statistics but you aren’t totally certain what career you want to pursue, this might be a good course choice for you. Mathematical and statistical skills are highly valued by employers and are easily transferable. Mathematical Sciences, with its three options, is the perfect way to study something you like, while having a chance to think about your eventual career choice.

Why Study Mathematical Sciences at UL?

The programme is suited to students with an aptitude for mathematics and statistics who are interested in applying their skills to problem solving in the real world. It is designed to provide a broad training that will allow you to work in any environment that requires strong analytical and problem solving skills. The programme involves an introductory two years, common to all students, when the fundamental mathematical and statistical tools are introduced. After two years, you will have the option of specialising in mathematics, statistics or computing. The programme also provides a theoretical grounding for students who wish to pursue postgraduate studies.

Entry route to Mathematical Sciences at UL is via LM124 Mathematics Common Entry.

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What you will study

The programme is full time, of four years in duration. It includes a period of Cooperative Education during the spring and summer of the third year of the course where the skills that you have acquired are applied in an appropriate workplace. The first two years of the course provide a foundation in a broad range of areas including calculus, statistics, linear algebra, discrete mathematics, operations research, mechanics, computer science and mathematical modelling.

There is also an elective pair of modules in the first year in either (a) Computer Science or (b) Economics or (c) Finance/Accounting or (d) Physics.

The third and fourth years of the programme give you the opportunity to specialise in one of the following options:

Mathematics

The mathematics stream is aimed at giving you a rounded appreciation of mathematics and the ability to approach problem solving with a mathematical mind. It develops the analytical skills acquired in the first two years using mathematical modelling of real world problems. Topics covered include linear algebra, fluid mechanics, dynamical systems, mathematical modelling and numerical solution of partial differential equations, perturbation methods, stochastic differential equations.

Statistics

Statistics deals with the collection, presentation, and analysis of data. Application areas include marketing, product development and testing, finance, economics, sociology, medicine, and the experimental sciences. Topics covered range from the mathematical basis of statistics through to the use of specialised software in the analysis of large, complex sets of data. The courses in this option include data analytics, statistical inference, statistical modelling, experimental design, quality control, time series analysis, stochastic processes and multivariate analysis.

Computing

The aim of this stream is to develop your understanding of the mathematical foundation of computing and to provide you with practical skills in the development of software systems. The courses in this option include systems analysis, data mining, algorithms, database systems and intelligent systems.

You will undertake a project in your final year that reflects your area of specialisation and, if possible, your Cooperative Education experience.

In Years 2, 3 or 4, students can apply to spend a semester studying abroad at one of our partner institutes worldwide.

For further details on options in Years 3 and 4, you can e-mail Norma Bargary.

  Semester 1   Semester 2
MS4021 Calculus 1 MS4022 Calculus 2
MS4131 Linear Algebra 1 MS4122 Further Linear Algebra
CE4701 Computer Software 1 MS4222 Intro. to Probabilty & Statistics
  Choose 2: CE4702 Computer Software 2
MS4101 Mathematics Laboratory   Choose 1:
AC4213 Financial Accounting AC4214 Accounting for Financial Decision Making
EC4111 Microeconomics EC4112 Macroeconomics
PH4051 Measure & Properties of Matter CS4182 Foundations of Computer Science 2
PH4131 Mechanics/Heat/Electricity/Magnetism PH4102 Wave/Light/Modern Physics
CS4221 Foundations of Computer Science 1    

 

  Semester 3   Semester 4
MS4043 Methods of Linear Analysis MS4014 Intro. to Numerical Analysis
MS4035 Probability Models MS4034 Applied Data Analysis
MS4403 Ordinary Differential Equations MS4303 Operations Research 1
MS4613 Vector Analysis MS4404 Partial Differential Equations
  One of: MS4414 Theoretical Mechanics
CS4013 Object Oriented Development    
MB4005 Analysis    

 

Semester 5 Title Semester 6 Title
MA4617 Introduction to Fluid Mechanics   Cooperative Education
MS4008 Numerical Methods for PDEs    
MS4045 Complex Analysis    
MS4105 Linear Algebra 2    
       
  Elective - choose 1    
CS4416 Database Systems    
MS4215 Advanced Data Analysis    
MS4217 Stochastic Processes    
MB4017 Geometry    

 

Semester 7 Title Semester 8 Title
MS4407 Perturbation Techniques & Asymptotics MS4018 Dynamic Systems
MS4627 Mathematics of Natural Phenomena MS4408 Mathematical Modelling
       
  Elective - choose 1   Elective - choose 1
MS4417 Project 1 MS4418 Project 2
MS4037 Statistical Data Science Project 1 MS4038 Statistical Data Science Project 2
       
  Elective - Choose 2   Elective - choose 2
CS4178 Software Requirements and Modelling CS4115 Data Structures and Algorithms
MS4027 Fundamentals of Financial Mathematics MS4028 Stochastic Differential Equations for Finance
MS4117 Discrete Mathematics 2 MS4218 Time Series Analysis
MS4315 Operations Research 2 MS4327 Optimisation
    MS4528 Mathematical and Statistical Models of Investments
Semester 5 Title Semester 6 Title
MS4105 Linear Algebra 2   Cooperative Education
MS4214 Statistical Inference    
MS4215 Advanced Data Analysis    
MS4217 Stochastic processes    
       
  Elective - choose 1    
MS4617 Introduction to Fluid Mechanics    
MS4008 Numerical Partial Differential Equations    
MB4017 Geometry    
CS4416 Database Systems    

 

Semester 7 Title Semester 8 Title
MS4037 Statistical Data Science Project 1 MS4038 Statistical Data Science Project 2
MA4007 Experimental Design MA4128 Advanced Data Modelling
MS4315 Operations Research 2 MA4708 Quality Control
    MS4218 Time Series Analysis
       
  Elective - choose 2   Elective - choose 1
MS4045 Complex Analysis MS4018 Dynamical Systems
MS4117 Discrete Mathematics 2 MS4028 Stochastic Differential Equations for Finance
MA4617 introduction to Fluid Mechanics (if not chosen in year 3) MS4327 Optimisation
MS4027 Fundamentals of Financial Mathematics MS4528 Mathematical and Statistical Models of Investments
CS4337 Big Data Management & Security CS4168 Data Mining
Semester 5 Title Semester 6 Title
CS4178 Software Requirements and Modelling   Cooperative Education
CS4416 Database Systems    
       
  Elective - choose 2    
MA4617 Introduction to Fluid Mechanics    
MS4008 Numerical Partial Differential Equations    
MS4045 Complex Analysis    
MS4105 Linear Algebra 2    
MS4017 Geometry    
       
  Elective - choose 1    
MS4214 Statistical Inference    
MS4215 Advanced Data Analysis    
MS4217 Stochastic processes    

 

Semester 7 Title Semester 8 Title
MS4117 Discrete Mathematics 2 MS4327 Optimisation
       
  Elective - choose 1   Elective - choose 1
MS4417 Project 1 MS4418 Project 2
MS4037 Statistical Data Science Project 1 MS4038 Statistical Data Science Project 2
       
  Elective - choose 3 modules total   Elective - choose 3 modules total
  Choose 1 or 2 from   Choose 1 or 2 from
CS4125 Systems Analysis and Design CS4006  Intelligent Systems
CS4337 Big Data Management & Security CS4115 Data Structures and Algorithms
    CS4815 Computer Graphics
    CS4084 Mobile Application Development
    CS4158 Programming Language Technology
    CS4168 Data Mining
       
  And choose 1 or 2 from   And choose 1 or 2 from
MS4007 Experimental Design MA4128 Advanced Data Modelling
MS4027 Fundamentals of Financial Mathematics MS4018 Dynamical Systems
MS4315 Operations Research 2 MS4028 Stochastic Differential Equations for Finance
MS4407 Perturbation Techniques and Asymptotics MS4218 Time Series Analysis
MS4627 Mathematics of Natural Phenomena MS4408 Mathematical Modelling
MA6011 Cryptographic Mathematics MS4528 Mathematical and Statistical Models of Investments

Entry requirements

Minimum grades

Applicants are required to hold the established Leaving Certificate (or an approved equivalent) with a minimum of six subjects which must include:

Two H5 (Higher Level) grades and Four O6 (Ordinary Level) grades or four H7 (Higher Level) grades. Subjects must include Mathematics, Irish or another language, and English.

Subject requirements

In addition, applicants must hold a minimum grade H3 in Mathematics.

Additional considerations

A Special Mathematics Examination will be offered at UL following the Leaving Certificate results for those students who did not achieve the Mathematics requirement.

We welcome applications from mature students. Mature applicants must apply through the Central Applications Office (CAO) by 1 February.

Application information for mature student applicants (PDF)

Non-EU Entry Requirements

How to apply

Where are you applying from? How to Apply
Ireland Irish students must apply to UL via the CAO. More information can be found here. 
The UK  Students who have completed their A-Levels can apply to UL via the CAO. More information can be found on the Academic Registry website. 
The EU EU Students can apply to UL via the CAO. More information can be found on the Academic Registry website.
Non-EU country If you are outside of the EU, you can apply for this degree here.

 

Fees and funding

Student course fees are broken into three components - Student contribution, Student Levy and Tuition Fees.

A number of illustrative examples of fees for this course based on the current fee levels have been set out in the tables below.

An explanation of the components, how to determine status and the criteria involved is provided below the examples as is a list of possible scholarships and funding available.

EU Students with Free fees status in receipt of a SUSI grant

HEA pays Tuition Fees €4,262
SUSI pays Student contribution €3,000
Student pays Student Levy €100
€7,362

EU Students with Free fees status not in receipt of a grant

HEA pays Tuition Fees €4,262
Student pays Student contribution €3,000
Student pays Student Levy €100
€7,362

Students with EU fee status not in receipt of a grant

Student pays Tuition Fees €4,262
Student pays Student contribution €3,000
Student pays Student Levy €100
€7,362

Non-EU Students

Student pays Tuition Fees €20,900
Student pays Student Levy €100
€21,000

Student course fees are comprised of the following components:

Student Contribution

Annual charge set by the government for all full-time third level students. All students are liable unless they have been approved for a grant by Student Universal Support Ireland (SUSI). Please refer to https://www.studentfinance.ie to determine your eligibility for a grant and for instructions on how to apply. The current student contribution is set at €3000.

Student Levy

All students are liable to pay the Student Levy of €100. Please note the Student Levy is not covered by the SUSI Grant.

Tuition Fees

These are based on Residency, Citizenship, Course requirements.

Review the three groups of criteria to determine your fee status as follows

  1. Residency
    • You must have been living in an EU/EEA member state or Switzerland for at least 3 of the 5 years before starting your course
  2. Citizenship
    • You must be a citizen of an EU/EEA member state or Switzerland or have official refugee status
  3. Course Requirements (all must be met)
    • You must be a first time full-time undergraduate (Exceptions are provided for students who hold a Level 6 or Level 7 qualification and are progressing to a Level 8 course in the same general area of study).
    • You must be undertaking a full-time undergraduate course of at least 2 year’s duration
    • You cannot be undertaking a repeat year of study at the same level unless evidence of exceptional circumstances eg serious illness is provided (in which case this condition may be waived)

Depending on how you meet these criteria your status will be one of the following -

  • Free Fee Status: You satisfy all three categories (1, 2 and 3) and therefore are eligible for the Higher Education Authority’s Free Fees scheme.
  • EU Fee Status: You satisfy the citizenship and/or residency criteria but fail to satisfy the course requirements and are liable to EU fees
  • Non EU Fee Status: You do not meet either the citizenship or residency criteria and are therefore liable to Non EU fees.

More information about fees can be found on the Finance website

These scholarships are available for this course

These scholarships are available for all courses

Your future career

Employability skills from this degree

  • Designing and conducting observational and experimental studies
  • Analysing and interpreting data, finding patterns and drawing conclusions
  • Approaching problems in an analytical and rigorous way, formulating theories and applying them to solve problems
  • Dealing with abstract concepts
  • IT skills
  • Advanced numeracy and analysing large quantities of data
  • Logical thinking

Further Study Options

Job titles for graduates with this degree

Graduates progressing directly into employment take up a wide variety of roles. The following provides a sample of initial roles listed on the Graduate Outcomes Survey by graduates approximately one year after graduation:

  • Actuary
  • Analytics Consultant
  • Business Analyst
  • Commodity Analyst
  • Marketing Analyst
  • Master Data/SRM Analyst
  • Risk Analyst
  • Software Engineer

Student Profiles

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Sarah Murphy

I chose UL for this course, but also because I’d never met a UL student who didn’t seem to love their time here. Maths and applied maths were my favourite subjects in school and this course seemed liked the perfect way to pursue those interests. For the first two years, you will establish a strong base in mathematics and statistics before specialising in your area of choice. In third year, you start to focus on your chosen specialty and then everyone goes on co-op placement. In your final year, you have the chance to pick a final year project in a topic that interests you.

This course has allowed me to develop essential skills needed to be a mathematician while also giving me the chance to apply them in a working environment. I completed my co-op placement in Analog Devices in Limerick, one of the leading semi-conductor companies in the world. I worked as a part of the New Product Engineering team that specialised in data analytics. My job involved the statistical analysis of data from different stages of testing and gave me the opportunity to apply the skills I had learned in college to the real world. My communication skills, presentation skills and my ability to work effectively as part of a team were vastly improved during my co-op experience.

I think one of the great advantages of studying Mathematical Sciences at UL is that it opens up a broad range of career paths. The course doesn’t tie you down to one profession but instead gives you the essential mathematical skills that are in demand in every sector.


 

Colm Howlin

I really enjoyed Maths in school, so I decided to continue with it at University. I visited several campuses before my making my decision on which University to choose. UL had by far the most impressive campus which made the decision easy.

As Principal Researcher at Realizeit, I lead the analytics and research efforts. Realizeit is an adaptive learning company that has created a platform to deliver personalised learning online to students. The platform uses data to figure out what works best for individual students and uses that to personalise and adapt the delivery of learning material.

I work on the development and deployment of the algorithms that are used by the system to personalise the learning experience. This ranges from algorithms that estimate the difficulty of a question to algorithms that automatically detect when a student is bored. I also work with several Universities to help them understand the impact of adaptive learning on how their students learn. My role, as with most in the tech sector, predominately involves problem-solving. The course not only provided me with the foundations in the tools that I would rely on in my career but more importantly, helped me develop my problem-solving skills.

Any advice for school leavers?

Study what you think you will enjoy, and you’ll set yourself up to have a far more successful and happier career than forcing yourself to study something that is supposed to lead to a good job or career.


 

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Kevin Brosnan

Throughout second level education numeracy based courses, maths and accounting, were my strongest - and not knowing what I could do with that my intention was always to become a second level maths teacher. After being encouraged by my maths teacher I looked at maths courses across Irish universities, and chose UL after speaking to a number of students on the course and after visiting the amazing campus.

The first two years formed a basis of maths, statistics and computing, but it was the third year which changed my career trajectory. My co-op placement was with Accenture Analytics in Dublin working with large enterprises to identify and prevent fraud using statistics and data, a field we now commonly call Data Science. After my co-op placement I was gripped by the thought of using statistics and computing to prevent fraud and risk. I finished my final year and then enrolled for a PhD at UL - during which time I investigated cheating in elite athletics and worked with a company developing fraud detection tooling in the Motor Insurance Space.

After finishing my PhD, I moved into the financial services space, and have worked with two global payment processors designing statistical and machine learning systems which detect, prevent and manage payment fraud in real-time - every transaction you do is scanned through a statistical model to evaluate the likelihood of the transaction being fraudulent in milliseconds!

Today I work on strategic risk management and product development, where I use my knowledge of fraud and risk, as well as mathematics and statistics, to protect companies and consumers from sophisticated fraud attacks. While I don’t write algorithms, or solve difficult equations, my background in logical thinking and understanding of data is essential to risk, design and strategic decisions I make every day.