Students
Tuition Fee
GBP 43,730
Per year
Start Date
2026-10-05
Medium of studying
On campus
Duration
9 months
Details
Program Details
Degree
Masters
Major
Applied Mathematics | Mathematics | Statistics
Area of study
Mathematics and Statistics | Natural Science
Education type
On campus
Timing
Full time
Course Language
English
Tuition Fee
Average International Tuition Fee
GBP 43,730
Intakes
Program start dateApplication deadline
2026-10-05-
2027-10-05-
About Program

Program Overview


MSc in Mathematical Sciences

The MSc in Mathematical Sciences provides a broad and flexible training in mathematical sciences, giving students with a keen interest in the mathematical sciences the chance to study a selection of interesting and varied master's-level courses.


About the Course

Oxford has a world-class reputation in the mathematical sciences, and this MSc, known as the Oxford Master's in Mathematical Sciences (OMMS), offers the opportunity to join Oxford's current fourth-year undergraduates and to work with an international group of peers, including other mathematical leaders of the future.


This course is not suitable for students whose primary focus is mathematical finance. These students should apply to the MSc in Mathematical and Computational Finance.


Course Structure

The course draws on subjects in mathematics, statistics, and computer science: from number theory, geometry, and algebra to genetics and mathematical physiology; from probability and mathematical geoscience to data mining and machine learning. Students have the opportunity to choose from many options, tailoring the programme to their individual interests and requirements. The course runs from the beginning of October through to the end of June.


Students can expect to learn a range of mathematics and/or statistics and to use this knowledge in the solution of complex problems in the mathematical sciences. The dissertation will provide an opportunity to develop research techniques as well as presentation and scientific communication skills.


Students will attend at least six units' worth of courses (with one unit normally corresponding to a 16-hour lecture course supported by classes) in addition to writing a dissertation (worth two units). Students will be encouraged to work collaboratively in classes, to develop their understanding of the material. Those wishing to extend themselves further might take one or two additional courses.


Attendance

The course is full-time and requires attendance in Oxford. Full-time students are subject to the University's Residence requirements.


Resources to Support Study

As a graduate student, students will have access to the University's wide range of resources, including libraries, museums, galleries, digital resources, and IT services.


Supervision

The allocation of graduate supervision for this course is the responsibility of the Mathematical Institute and the Department of Statistics, and it is not always possible to accommodate the preferences of incoming graduate students to work with a particular member of staff. Under exceptional circumstances, a supervisor may be found outside the Mathematical Institute and the Department of Statistics.


Assessment

The majority of lecture courses on the MSc are assessed by invigilated written examinations, although a minority of courses are assessed by a take-home exam known as a mini-project. The dissertation work culminates in a written report that constitutes two of the minimum eight units required to complete the course.


Graduate Destinations

Recent graduates of the MSc have taken on roles in a variety of industries, including finance, software engineering, education, and scientific research. The MSc also provides good preparation for doctoral studies, and some graduates have taken this route.


Course Components

Compulsory Study

Students will write a dissertation under the guidance of a supervisor. This will typically involve investigating and writing in a particular area of mathematical sciences, without the requirement (while not excluding the possibility) of obtaining original results.


Options

Students will be required to take between six and eight option courses, which they will be able to choose from a range in mathematics, physics, and statistics.


  • C1.1 Model Theory
  • C1.2 Gel's Incompleteness Theorems
  • C1.3 Analytic Topology
  • C1.4 Axiomatic Set Theory
  • C2.2 Homological Algebra
  • C2.3 Representation Theory of Semisimple Lie Algebras
  • C2.4 Infinite Groups
  • C2.5 Non-Commutative Rings
  • C2.6 Introduction to Schemes
  • C2.7 Category Theory
  • C3.1 Algebraic Topology
  • C3.2 Geometric Group Theory
  • C3.3 Differentiable Manifolds
  • C3.4 Algebraic Geometry
  • C3.5 Lie Groups
  • C3.6 Modular Forms
  • C3.7 Elliptic Curves
  • C3.8 Analytic Number Theory
  • C3.9 Computational Algebraic Topology
  • C3.10 Additive Number Theory
  • C3.11 Riemannian Geometry
  • C3.12 Low-Dimensional Topology and Knot Theory
  • C4.1 Further Functional Analysis
  • C4.3 Functional Analytic Methods for PDEs
  • C4.6 Fixed Point Methods for Nonlinear PDEs
  • C4.7 Fourier Analysis
  • C4.9 Optimal Transport and Partial Differential Equations
  • C5.1 Solid Mechanics
  • C5.2 Elasticity and Plasticity
  • C5.4 Networks
  • C5.5 Perturbation Methods
  • C5.6 Applied Complex Variables
  • C5.7 Topics in Fluid Mechanics
  • C5.9 Mathematical Mechanical Biology
  • C5.11 Mathematical Geoscience
  • C5.12 Mathematical Physiology
  • C6.1 Numerical Linear Algebra
  • C6.2 Continuous Optimisation
  • C6.4 Finite Element Method for PDEs
  • C6.5 Theories of Deep Learning
  • C7.1 Theoretical Physics
  • C7.4 Introduction to Quantum Information
  • C7.5 General Relativity I
  • C7.6 General Relativity II
  • C7.7 Random Matrix Theory
  • C8.1 Stochastic Differential Equations
  • C8.2 Stochastic Analysis and PDEs
  • C8.3 Combinatorics
  • C8.4 Probabilistic Combinatorics
  • C8.7 Optimal Control
  • SC1 Stochastic Models in Mathematical Genetics
  • SC2 Probability and Statistics for Network Analysis
  • SC4 Advanced Topics in Statistical Machine Learning
  • SC5 Advanced Simulation Methods
  • SC6 Graphical Models
  • SC7 Bayes Methods
  • SC9 Probability on Graphs and Lattices
  • SC10 Algorithmic Foundations of Learning
  • SC11 Climate Statistics

Entry Requirements

Proven and Potential Academic Excellence

The requirements described below are specific to this course and apply only in the year of entry that is shown.


  • A first-class undergraduate degree with honours in mathematics, statistics, data science and machine learning, or a related discipline.
  • For applicants with a degree from the USA, the minimum overall GPA that is normally required to meet the undergraduate-level requirement is 3.7 out of 4.0.
  • Research or work experience in the proposed area of specialisation may be an advantage.
  • Publications are not expected.

English Language Proficiency

This course requires proficiency in English at the University's higher level. If the first language is not English, evidence that meets this requirement may be needed.


Funding

For entry in the academic year, the collegiate University expects to offer over 1,100 full or partial graduate scholarships across a wide range of graduate courses.


Costs

Annual Course Fees

The fees for this course are charged on an annual basis.


  • Home: 」16,220
  • Overseas: 」43,730

Additional Costs

There are no compulsory elements of this course that entail additional costs beyond fees and living costs. However, as part of the course requirements, students may need to choose a dissertation, a project, or a thesis topic, which may incur additional expenses.


Living Costs

In addition to course fees and any additional course-specific costs, students will need to ensure they have adequate funds to support their living costs for the duration of their course.


  • The range of likely living costs for a single, full-time student is between 」1,405 and 」2,105 for each month spent in Oxford.

College Preference

Students enrolled on this course will belong to both a department/faculty and a college. The following colleges accept students on the MSc in Mathematical Sciences:


  • Balliol College
  • Brasenose College
  • Christ Church
  • Exeter College
  • Hertford College
  • Jesus College
  • Keble College
  • Kellogg College
  • Lady Margaret Hall
  • Linacre College
  • Lincoln College
  • Magdalen College
  • Mansfield College
  • New College
  • Oriel College
  • Pembroke College
  • The Queen's College
  • Reuben College
  • St Anne's College
  • St Catherine's College
  • St Cross College
  • St Edmund Hall
  • St Hilda's College
  • St Hugh's College
  • St John's College
  • St Peter's College
  • Somerville College
  • Trinity College
  • Wadham College
  • Worcester College
  • Wycliffe Hall

How to Apply

Our guide to getting started provides general advice on how to prepare for and start an application.


  • An application fee of 」75 is payable for each application to this course.
  • Application fee waivers are available for applicants from low-income countries, refugees and displaced persons, UK applicants from low-income backgrounds, and applicants who applied for our Graduate Access Programmes in the past two years and met the eligibility criteria.

Completing the Application

Students should refer to the information below when completing the application form, paying attention to the specific requirements for the supporting documents.


  • Proposed field and title of research project: Please enter the preferred subject area from the list provided.
  • Proposed supervisor: It is not necessary to identify a potential supervisor in the application.
  • Referees: Three overall, at least two of which must be academic.
  • Official transcript(s): Should give detailed information of the individual grades received in university-level qualifications to date.
  • Contextual statement: If provided, will be used as part of an initiative to contextualise applications at the different stages of the selection process.
  • Statement of purpose: A maximum of 600 words, explaining motivation for applying, relevant experience and education, and specific areas of interest.
See More
How can I help you today?