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Coding Your Future: A Guidebook for Students

40 Your Story

Any internship or placement you do will help your CV stand out from the crowd. Any experience you get before you graduate will be a key part of your story enabling you to build your knowledge, improve your skills and gain professional experience through paid employment. We talked about where to look for these opportunities in chapter 11, the vacancies listed below are taken from Career Connect, login required see section 11.3.1.

40.1 Paid summer internships in engineering

Are you studying Computer Science at The University of Manchester? The School of Engineering has over 40 paid summer internships for undergraduate students. Apply below by 23rd February, check the eligibility criteria for each post and general requirements in section 40.2. Projects are supervised by academics from across the School of Engineering reflecting a wide range of teaching and research across the University. Any of these internships would be a great addition to help your CV stand out in future.

The School of Engineering at the University of Manchester.

Figure 40.1: The School of Engineering at the University of Manchester.

Sharpen your engineering skills and deepen your knowledge by tackling important problems in physics, chemistry, biology, medicine, materials, robotics, AI, computer science, machine learning and more. These projects come with unique flavours of computation and some magnificent Mancunian software:

40.1.1 Department of Computer Science

Internships in the Department of Computer Science

  1. Developing Practical Tutorials for the MSc Unit in AI Security and Privacy, with Edoardo Manino, see bit.ly/SOEWNYZL
  2. Exploring Magnetisation Dynamics using Scientific Software with Mara Strungaru see bit.ly/SOELXVLY
  3. Developing material to support the development of a new MSc course unit - Data Engineering Concepts, with Sandra Sampaio see bit.ly/SOE8QYEY
  4. Supporting the Move to RISC-V Teaching in Computer Science with Paul Nutter see bit.ly/SOE4JL8G
  5. Software Development - Machine Learning for Biological Data Processing with Hongpeng Zhou, see bit.ly/SOEGO4N6
  6. Clinical Text Data Generation with Large Language Models, with Goran Nenadic, see bit.ly/SOEKX4X6
  7. Domain Adaptation in Generative Modelling for AI for Science with Dmitry Kangin see bit.ly/SOE9VYG6
  8. Extending and Improving a Processor simulator for Teaching Computer Architecture, with Pavlos Petoumenos see bit.ly/SOE8QYOY
  9. AI Mentors in Action: Developing Custom GPTs for Enhanced University Learning and Support with Christoforos Moutafis, see bit.ly/SOE8QYKO
  10. Computer Cyber Security Scripted Lab with John Goodacre, see bit.ly/SOEKXBGD
  11. Data Curation Driven by Modern AI Techniques with Jiaoyan Chen, see bit.ly/SOE8QGV8
  12. Exploring Semantical Distance for Generating Adversarial Examples Though a Probabilistic Perspective with Andi Zhang, see bit.ly/SOEBNO82
  13. Development Resources for COMP67202: Mobile and Ubiquitous computing with Sarah Clinch, see bit.ly/SOELXV8G
  14. Developing custom instrumentation to measure electrical resistance, with Tom Thomson, see bit.ly/SOEGO4MZ
  15. Developing Learning Resources for the new Text Mining postgraduate unit with Riza Batista-Navarro see bit.ly/SOEGO4VZ
  16. Vision and Language-guided Real-time Emotional Text Generation for Human-Robot Interaction with Rahul Singh Maharjan see bit.ly/SOE4JY2Z
  17. Domain-Specific LLM for Spintronics: Specialized AI for Advanced Materials Research with Andre Freitas, see bit.ly/SOE6VZL8
  18. Ongoing Development of COMP16321 & COMP23111 Interactive Lab Platforms with Gareth Henshall, see bit.ly/SOEBN4B4
  19. TornadoVM Support for Software Development Kit Managers with Christos Kotselidis see bit.ly/SOE6VQA7

40.1.2 Department of Electrical and Electronic Engineering

Internships in the Department of Electrical and Electronic Engineering

  1. Development of a Visuo-Haptic Recognition System to Enhance Robotic Perception with Xiaoxiao Cheng, see bit.ly/SOE4JY3M
  2. UAV Image Processing for Aerial Surveys and Object Detection with Hujun Yin, see bit.ly/SOELXV6E
  3. Sustainable Agriculture in Africa - Android App for Control of Multispectral Sensor with Bruce Grieve, see bit.ly/SOEM8VDN
  4. Inverse Design of Photonic Devices with Joel Loh, see bit.ly/SOEZXWJB

40.1.3 Department of Mechnical, Aerospace & Civil Engineering

Internships in the Department of Department of Mechnical, Aerospace & Civil Engineering (MACE)

  1. How Conflicts Harm Future Resilience, with Ben Parkes, see bit.ly/SOE8QYMO
  2. Developing Aerospace Engineering Databases from Sparse Data, with Antonino Filippone, see bit.ly/SOEKX492,
  3. Assessing the impacts of climate change on sport in Greater Manchester, with Ruth Wood, see bit.ly/SOEWNYKJ
  4. Path Planning for Multi Modal Vehicle with Pawel Ladosz, see bit.ly/SOEGO433
  5. Explainable AI vs Turbulence - Symbolic Machine Learning for the Turbulence Impact at Gas-Liquid Interface with Tianning Tang, bit.ly/SOEWNYAL
  6. Investigation of Conditions at a Site Suitable for Tidal Energy Extraction, with Hannah Mullings, see bit.ly/SOEWNYNL
  7. Development of a Digital Tool That Can Be Used in Engineering Project Management with Paul Baguely, see bit.ly/SOE8QY2Y
  8. Advancing EDI in The School of Engineering: A Data-Driven Approach to Bridging the Gender Gap, with Hannah Mullings, see bit.ly/SOE6VQVJ
  9. Development of Interactive Aerospace Engines Exhibit for the Nancy Rothwell Building, with Kate Smith , see bit.ly/SOEZXWXB
  10. Planetary Exploration Rover with Kate Smith see bit.ly/SOEM8V83
  11. Developing Teaching and Learning Resources to Support MSc Management of Projects Programmes, Elika Aminian see bit.ly/SOE9VYV6
  12. Development of a Generative AI solution to cost modelling, with Paul Baguely, see bit.ly/SOEGO466
  13. Modelling of Drag for Very Low Earth Orbit Satellites with Peter Roberts, see bit.ly/SOEGO4D4
  14. Feasibility of Residential Electric Vehicle Charging Station Using Solar Energy with Kamal Qazi, see bit.ly/SOEKXBED
  15. GPU optimisation of a numerical method for magnetohydrodynamic flow simulations with Alessandro De Rosis, see bit.ly/SOEBN4E4
  16. Machine Learning for Irrigation Mapping in Data-Sparse Regions with Tim Foster, see bit.ly/SOE4JYAZ

40.1.4 Department of Chemical Engineering

Internships in the Department of Chemical Engineering

  1. Developing a Future-Ready E-Portfolio Platform for Higher Education Students with Salman Shahid, see bit.ly/SOE6VQEJ
  2. Designing AI-Enhanced Assessment Rubrics for Chemical Engineering Education, with Salman Shahid, see bit.ly/SOEGO4Q6
  3. Designing Sustainability-Themed Outreach Activities for Teachers and Public Engagement with Wennie Subramonian, see bit.ly/SOE9VY86
  4. Development of a Digital Twin for Practical Teaching, with Bernard Treves Brown, see bit.ly/SOE4JYGM
  5. Physics-Based Machine Learning Assisted Optimisation of Pressure Swing Adsorption for Carbon Capture, with Jie Lie, see bit.ly/SOELXVEY
  6. Innovate or Standardize? Creating educational diversity in a system of homogeneous practice with Flor Siperstein, see bit.ly/SOE6VZB3
  7. Enzymatic N-N bond formation for biosynthetic drug synthesis by nonheme iron oxygenases with Sam De Visser see bit.ly/SOE8QYAO

40.2 Eligibility

All students must remain working in the UK for the duration of the internship and most internships will be fully based on campus. Some internships may have an option to complete part remotely - please check individual project descriptions for more information.

There are many different projects to choose from, each with different supervisors and very different project outlines that you could be working on over the summer. By applying for one of our internships you are giving yourself a chance to develop your technical and transferable skills whilst gaining experience of working with an accomplished academic on a project that you are inspired by.

Applications will be reviewed following the closing date and shortlisted candidates will be contacted and invited to the next stage of the process, which will be a video interview that will be reviewed by the project supervisor.

The scheme is open to registered Year 2 undergraduate students on a 3- or 4-year programme, as well as Year 3 undergraduate students on a 4-year programme. You may be on a BEng or MEng programme, and both home and international students are welcome to apply.

You may only apply to a maximum of 3 internships (unless you are in receipt of a bursary or financial support from the University, in which case, you may choose to apply for more). These SoE internships are open to students from multiple disciplines within the School of Engineering. Please see each advert for further information on which disciplines can apply.

Students who have previously undertaken an internship through this scheme are unfortunately not eligible to apply again. The purpose of the scheme is to provide valuable and relevant work experience that Engineering students can include on their CVs, which in turn should increase the chances of securing external opportunities at a later point. In summary:

  • You must be 2nd or 3rd year student at the University of Manchester with at least 1 full year of your programme remaining, i.e. you must be a Year 2 student on any length programme or a Year 3 student on a 4-year programme.
  • You must check you are eligible for each specific project; each project will require a different range of students and skills.
  • You can apply for maximum of 3 internships unless you are in receipt of a bursary or financial support from the University. If you have undertaken a School of Engineering internship in the past, you are NOT eligible to apply.
  • To improve your chances of success, make sure you Debug Your CV using the checklist in section 8.6
  • To improve your chances of success, make sure you also complete the CV Essentials Pathway at www.careers.manchester.ac.uk/services/ondemand/pathways/

Questions about the internships programme can be emailed to .