Mathematics (Climate Science) - University of E

Tuition Fee

GBP 27,000

Per year

Start Date

Medium of studying

Duration

48 months

Program Facts

About Program

About University

Admission Requirements

Gallery

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Program Facts

Program Details

Degree

Masters

Major

Atmospheric Science | Meteorology

Area of study

Natural Science

Timing

Full time

Course Language

English

Tuition Fee

Average International Tuition Fee

GBP 27,000

About Program

Program Overview

The MSci Mathematics (Climate Science) program at the University of Exeter combines mathematical modelling, fluid dynamics, and statistics to provide students with an in-depth understanding of climate science. The program prepares graduates for careers in climate-related fields, research and development, and other sectors requiring strong mathematical skills. It also offers opportunities for paid work experience, study abroad, and proficiency in a second subject.

Program Outline

MSci Mathematics (Climate Science) - University of Exeter

Degree Overview:

This program is designed for students passionate about mathematics and its applications in climate modeling.

Key Features:

Focus on Climate Science: The program emphasizes the application of mathematics to climate modeling, a crucial aspect of understanding and addressing global climate change.
Chartered Mathematician Designation: The program is accredited by the Institute of Mathematics, meeting the educational requirements for the Chartered Mathematician designation.
Practical Experience: Students have the option to take the "Commercial and Industrial Experience" module during the vacation before their third year, allowing them to gain paid work experience in a commercial setting while earning credits towards their degree.

Outline:

Year 1:

Compulsory Modules:
Mathematical Structures (MTH1001):
Mathematical Methods (MTH1002): Covers essential mathematical methods and techniques.
Mathematical Modelling (MTH1003): Explores the application of mathematical models to real-world problems.
Probability, Statistics and Data (MTH1004): Introduces probability theory, statistical methods, and data analysis.
Foundations (MTH1000): Provides support for background knowledge from A-level, particularly for students who did not take Further Mathematics.

Year 2:

Compulsory Modules:
Differential Equations (MTH2003):
Vector Calculus and Applications (MTH2004): Explores vector calculus and its applications in various fields.
Optional Modules:
Real Analysis (MTH2008):
Complex Analysis (MTH2009): Explores the theory of complex numbers and functions.
Groups, Rings and Fields (MTH2010): Introduces abstract algebra concepts like groups, rings, and fields.
Linear Algebra (MTH2011): Covers the theory and applications of linear algebra.
Modelling: Theory and Practice (MTH2005): Provides a deeper understanding of mathematical modeling techniques.
Statistical Modelling and Inference (MTH2006): Focuses on statistical modeling and inference methods.
Free Choice (XXXXXX): Students can choose up to 30 credits from any discipline in the University, subject to approval, prerequisites, timetabling, and availability.

Year 3:

Compulsory Modules:
Fluid Dynamics (MTH3007):
Mathematics of Climate Change (MTH3030): Focuses on the mathematical aspects of climate change.
Computational Nonlinear Dynamics (MTH3039): Introduces computational methods for analyzing nonlinear systems.
Research in Mathematical Sciences (MTHM036): Provides an introduction to research methods in mathematics.
Theory of Weather and Climate (MTH3001): Covers the theoretical foundations of weather and climate.
Optional Modules:
Number Theory (MTH3004):
Mathematical Biology and Ecology (MTH3006): Applies mathematical methods to biological and ecological problems.
Partial Differential Equations (MTH3008): Covers the theory and applications of partial differential equations.
Nonlinear Systems and Control (MTH3011): Explores the analysis and control of nonlinear systems.
Applied Differential Geometry (MTH3013): Introduces differential geometry and its applications.
Mathematics: History and Culture (MTH3019): Explores the historical and cultural context of mathematics.
Graphs, Networks and Algorithms (MTH3022): Covers graph theory, network analysis, and algorithms.
Stochastic Processes (MTH3024): Introduces the theory and applications of stochastic processes.
Cryptography (MTH3026): Explores the mathematical principles behind cryptography.
Statistical Inference: Theory and Practice (MTH3028): Focuses on statistical inference methods and their applications.
Galois Theory (MTH3038): Covers Galois theory and its applications in algebra.
Topology and Metric Spaces (MTH3040): Introduces topological concepts and metric spaces.
Bayesian statistics, Philosophy and Practice (MTH3041): Explores Bayesian statistics and its philosophical foundations.
Integral Equations (MTH3042): Covers the theory and applications of integral equations.
Bayesian Data Modelling (MTH3044): Introduces Bayesian methods for data modeling.
Statistical Computing (MTH3045): Covers computational methods for statistical analysis.
Functional Analysis (MTH3050): Explores the theory of functional analysis.
Commercial and Industrial Experience (EMP3001): Provides an opportunity for paid work experience in a commercial setting.
Free Choice (XXXXXXX): Students can choose up to 30 credits from any discipline in the University, subject to approval, prerequisites, timetabling, and availability.
Aerosols, Clouds and Climate (NSC3009): Explores the role of aerosols and clouds in climate.

Final Year:

Compulsory Modules:
Fluid Dynamics of Atmospheres and Oceans (MTHM019):
Modelling the Weather and Climate (MTHM023): Covers advanced methods for modeling weather and climate.
MSci Project (MTHM040): Students undertake an independent research project under the supervision of a faculty member.
Optional Modules:
Functional Analysis (MTHM001):
Fractal Geometry (MTHM004): Explores the theory and applications of fractal geometry.
Mathematical Theory of Option Pricing (MTHM006): Introduces mathematical models for option pricing.
Advanced Topics in Mathematical & Computational Biology (MTHM009): Covers advanced topics in mathematical and computational biology.
Representation Theory of Finite Groups (MTHM010): Explores the representation theory of finite groups.
Advanced Topics in Statistics (MTHM017): Covers advanced topics in statistical theory and methods.
Dynamical Systems and Chaos (MTHM018): Explores the theory and applications of dynamical systems and chaos.
Algebraic Number Theory (MTHM028): Covers algebraic number theory and its applications.
Algebraic Curves (MTHM029): Explores the theory of algebraic curves.
Waves, Instabilities and Turbulence (MTHM030): Covers the theory and applications of waves, instabilities, and turbulence.
Magnetic Fields and Fluid Flows (MTHM031): Explores the interaction between magnetic fields and fluid flows.
Statistical Modelling in Space and Time (MTHM033): Covers statistical models for spatial and temporal data.
Analytic Number Theory (MTHM041): Covers analytic number theory and its applications.
Space Weather and Plasmas (MTHM045): Explores the physics of space weather and plasmas.
Ergodic Theory (MTHM048): Covers ergodic theory and its applications.
Mid-Latitude Weather Systems (MTHM052): Explores the dynamics of mid-latitude weather systems.
Mathematical Modelling in Biology and Medicine (NSCM005): Applies mathematical models to biological and medical problems.
Modules in Geography (GEOMXXX): Students can choose modules from the Geography department.
Data-driven Analysis and Modelling of Dynamical Systems (MTHM062): Covers data-driven methods for analyzing and modeling dynamical systems.
Uncertainty Quantification (MTHM063): Explores methods for quantifying uncertainty in mathematical models.
Free Choice of Level M Module (XXXMXXX): Students can choose up to 30 credits from any level M module in the University.
Free Choice of Level 3 Module (XXX3XXX): Students can choose up to 15 credits from any level 3 module in the University.

Assessment:

Combination of Examinations and Coursework: Assessment is through a combination of examinations and coursework.
Emphasis on Examinations: Examinations are the primary component of assessment.
Coursework for Steady Progress: Coursework helps students to work steadily throughout the degree, particularly important in mathematics where the subject matter develops logically.
Written Examinations: Written examinations are held in January and May/June of the first and second years and in May/June of each subsequent year.
Other Assessment Methods: Some modules may include tests, essays, presentations, and/or project reports.

Teaching:

Combination of Teaching Methods: The program utilizes a combination of teaching methods, including lectures, seminars, examples classes, workshops, and tutorials.
Lectures: Most modules involve three one-hour lectures per week.
Tutorials: Tutorial classes are held every fortnight for most modules, except for those involving computing or project work.
Private Study: Students are expected to spend about 20 hours per week in private study.
Personal Tutors: Each student is assigned a personal tutor for guidance and support.
Research and Practice-Led Culture: The program is taught by internationally recognized mathematicians, scientists, and practitioners active in various fields of pure and applied mathematics, statistics, and applications.
Research Opportunities: Students have opportunities to become involved in research projects, including the independent research project in the final year.

Careers:

Mathematical Modelling Skills: The program develops mathematical modeling skills that are highly sought after in various research and development roles.
Climate-Related Careers: Graduates are well-suited for careers in companies concerned with climate, such as crop production, energy suppliers, and environmental consultants.
Strong Employment Record: The University of Exeter has a strong employment record and graduates excel in specialist mathematical fields and across a broad range of other sectors.
Employer Engagement: The university hosts events with local and national employers, including mock interviews, CV workshops, drop-ins, and lectures.
Careers Service: The university's Careers Service provides support for career exploration and job searching.
Professional Experience: Students can gain paid work experience in a commercial setting through the "Commercial and Industrial Experience" module.
Career Paths: Graduates pursue careers in various fields, including:
Accountant
Actuary
Analyst Programmer
Business Analyst
Credit Risk Analyst
Data Science Developer
Investment Analyst
Software Engineer
Statistician
Tax Manager

Other:

Study Abroad: Students have the opportunity to study abroad at partner universities in Europe, USA, Canada, Australia, and China.
Supportive Department: The department prioritizes contact time between students and staff.
Proficiency in a Second Subject: Students can gain proficiency in a second subject, such as a foreign language, data science, entrepreneurship, innovation, law, leadership, or social data science, by completing 60 credits in that subject.

UK students: £9,250 per year International students: £27,000 per year

Mathematics (Climate Science) MSci