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Durham University

Department of Mathematical Sciences

Post Exam Activities

Below is a list of activities taking place after the May/June 2018 exam period, including induction sessions for those students progressing to the next level of study.

Induction Sessions

Monday 18 June

10am - 12pm


For students progressing to Level 2.

1pm - 3pm


For students progressing to Level 3.

3pm - 5pm


For students progressing to Level 4.

Academic Advisor Meetings

Thursday 21 & Friday 22 June

Your advisor will be in touch with you to arrange a specific time for meeting with you at the end of this term. The purpose of this advisor meeting is to give you advice on selecting modules for next year, to discuss how the year has gone for you, and to discuss any other questions you may have (career, references, etc.).

Lectures & Workshops

Please note, this list is not complete and details will be updated in the coming weeks.

Monday 4 June

2pm - 4pm, CG93

Writing Your Mathematics Project

Philip Nathan


This session is aimed at supporting you in the writing up of your mathematics project. The session will focus on the persuasive and rhetorical nature of maths project writing, including rhetorical aspects of introduction and conclusion writing in the Maths project, as well as focusing on other structural elements of the project. The characteristics of effective maths project writing will be addressed. The session will be supported and ideas illustrated using writing from previous successful maths projects. More general tips and advice will also be provided about mathematics project writing and writing in general.

Tuesday 19 June

Session 1: 10am - 12pm, CM105

Session 2: 1pm - 3pm, CM105

*students should attend both sessions

A topic in probability: Random walks

Dr Hugo Lo


"Basic probability theory deals with events and their probabilities, and random variables and their distributions, describing ‘static’ experiments where randomness plays a role. More advanced probability models deal with processes evolving randomly over time, or ‘dynamic’ experiments. A basic object describing such a situation is a stochastic process, which is just a sequence of random variables. A famous example is the random walk. In this activity, we will investigate the long-term behaviour of a simple random walk, using a bit of combinatorics, a bit of analysis, and some probability theory. This topic is not covered in our undergraduate courses, but there are connections to Markov chains from Probability II, renewal theory from Probability III/IV, martingales from Stochastic Processes III/IV, and a topic in Project IV."

Interested students should contact to confirm attendance.