Master of Engineering (MEng)

MEng Mechatronic Engineering

*This course is now closed for applications for 2025 entry.

  • Duration: 4 years
  • Year of entry: 2025
  • UCAS course code: HHH6 / Institution code: M20
  • Key features:
  • Scholarships available
  • Accredited course

Full entry requirementsHow to apply

Fees and funding

Fees

Tuition fees for home students commencing their studies in September 2025 will be £9,535 per annum (subject to Parliamentary approval). Tuition fees for international students will be £34,000 per annum. For general information please see the undergraduate finance pages.

Policy on additional costs

All students should normally be able to complete their programme of study without incurring additional study costs over and above the tuition fee for that programme. Any unavoidable additional compulsory costs totalling more than 1% of the annual home undergraduate fee per annum, regardless of whether the programme in question is undergraduate or postgraduate taught, will be made clear to you at the point of application. Further information can be found in the University's Policy on additional costs incurred by students on undergraduate and postgraduate taught programmes (PDF document, 91KB).

Scholarships/sponsorships

The University of Manchester is committed to attracting and supporting the very best students. We have a focus on nurturing talent and ability and we want to make sure that you have the opportunity to study here, regardless of your financial circumstances.

For information about scholarships and bursaries please visit our undergraduate student finance pages and our Department funding pages .

Course unit details:
Mathematics 1E2

Course unit fact file
Unit code MATH19622
Credit rating 10
Unit level Level 1
Teaching period(s) Semester 2
Available as a free choice unit? No

Pre/co-requisites

Pre-requisite unit: MATH19611 Mathematics for EEE 1E1

Aims

Provide students in EEE with appropriate mathematical techniques (multivariate calculus and probability) for use within other course units. 

Learning outcomes

-Find the partial derivatives of a function of two or more variables and use the results to find local and global maxima and minima of the function including those satisfying further constraints.

-Find the divergence or curl of a vector function ; find the gradient of a scalar function

-Using Jacobians and other techniques, find integrals involving functions of two or more variables.

-Show that certain functions satisfy particular integral or differential theorems.

-Analyse and interpret data using descriptive statistics, data visualisation, and simple linear regression techniques.

-Explain basic concepts in probability and probability distributions, and apply them to formulate and solve engineering problems. 

Syllabus

5 hours : Partial Differentiation: Scalar functions, differentiation, partial derivatives, gradient and directional derivatives, Extrema of real-valued functions. Constrained extrema and Lagrange multipliers. Vector fields. Gradient, divergence and curl. Laplacian. Identities.

2 hours : Multiple Integrals: Double integral over a rectangle, double integral over general regions. Triple integral.

6 hours : Integrals over Lines and Surfaces: Parameterized lines and surfaces. Path integral. Area of a surface. Integral of scalar function over surfaces. Integral of vector function over surfaces. Green's Theorem in the Plane. Stokes Theorem. Conservative fields. Gauss Theorem. Maxwell’s Equations.

4 hours : Statistics: Discrete and continuous data. Measure of central tendency: mean, mode, median. Measure of spread: range, variance, standard deviation. Histogram and frequency curve. Properties and applications of normal curves. Correlation and simple linear regression.

5 hours : Probability: Empirical and classical probability. Addition and multiplication laws of probability. Random variables and probability distributions. Mean and standard deviation. Binomial and Poisson distribution. Normal distribution and area under normal distribution curves. 

Assessment methods

Method Weight
Written exam 80%
Written assignment (inc essay) 20%

Feedback methods

Two separate written assignment/coursework. Feedback method: Instant through feedback system

Recommended reading

Engineering mathematics

Srimanta Pal, Subodh Chandra Bhunia.

OUP


Helping Engineers Learn Mathematics : https://www.mub.eps.manchester.ac.uk/helm/

University of Manchester Mathematical Formula Tables : https://personalpages.manchester.ac.uk/staff/colin.steele/formtabsV2.pdf

 

Engineering mathematics

K.A. Stroud with Dexter J. Booth.

Eighth edition. Red Globe Press

Advanced Engineering mathematics

K.A. Stroud with Dexter J. Booth.

Eighth edition. Red Globe Press

 

Engineering mathematics : a foundation for electronic, electrical, communications and systems engineers

Anthony Croft, Robert Davison, Martin Hargreaves and James Flint

Fourth edition. Pearson


Introduction to Probability and Statistics for Engineers and Scientists, Sheldon Ross, Academic Press 
 

Study hours

Scheduled activity hours
Lectures 22
Tutorials 11
Independent study hours
Independent study 67

Teaching staff

Staff member Role
Igor Chernyavsky Unit coordinator

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