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Department of Mathematics

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Current students

Information for current PhD students

Milestones

Milestones aims to help PhD students keep their study on track, receive feedback on their progress and apply the recommendations to improve their research.

Find out more about Milestones

PG Forum Poster Competition

Mathematics PhD students are invited to submit posters summarising their research to the annual departmental PG Poster Competition.

Find out more about the PG Forum

Doris Chen Scholarship

The Doris Chen PhD Award comprises the Mobility Fund, the Reward Merit and the Hardship Fund.

Find out more about the scholarship

Imperial students

The College students web pages have all kinds of invaluable information for current PhD students - from careers support to well being; research integrity courses to term dates.

Visit Imperial students

Maths PhD links

  • Handbook 2020-21 (PDF)
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Further information

Current students

  • Access programme details for your course: undergraduate and postgraduate taught / postgraduate research
  • Find out more about academic year 2020-21

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Search for courses in the 2021-22 online prospectus: undergraduate / postgraduate taught / postgraduate research


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Terms and conditions

Important information that you need to be aware of both prior to becoming a student, and during your studies at Imperial College: Terms and conditions

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Section Information

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Department of Mathematics

Huxley Building
South Kensington Campus
Imperial College London
London
SW7 2AZ

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Email us with a general enquiry >

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Mathematics sections enquiries

Applied section:

Martin Cooper

Pure section:
Magda Vidler

Mathematical Finance section:
Rula Murtada

Statistics section:
Arianna Saccani

Student enquiries

Email us regarding:

Undergraduate admissions >

Undergraduate general queries >

MSc enquiries >

PhD enquiries >

Maths Centres for Doctoral Training enquiries

Geometry and Number Theory:

Nicky Townsend

Mathematics of Planet Earth Centre:
Barsha Shrestha

Mathematics of Random Systems:
Lydia Noa

Modern Statistics & Statistical Machine Learning: 
Vanessa Eyles

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