Research Assistant For Web Development And Implementation

We're looking for three students to help develop induction courses for new teaching staff about digital learning tools at QMUL. You'll work directly with the Technology Enhanced Learning (TEL) team to create training materials that help staff use technology effectively in their teaching. 

Main Responsibilities

1. Help create online self-paced training courses for new teaching staff 
2. Assist in developing in-person induction sessions for new teaching staff 
3. Participate in creating student case study videos 
4. Share your experience with digital learning tools at QMUL 
5.  Provide student perspective on how teaching staff can better use technology 

This is an exciting opportunity to gain:

• Professional experience in digital education 
• Content development skills 
• Project collaboration experience 
• Understanding of educational technology at Queen Mary 
• Opportunity to represent the student voice in the development of digital learning initiatives.
• The training provided can enhance your CV and develop transferable skills. 

Your input will help shape how new teaching staff learn to use technology in their classes. You'll represent student voices in improving digital education at QMUL while gaining valuable professional experience. 

Time Commitment: 10-15 hours per week for approx. 3 months

Currently enrolled at QMUL 

Essential

1. Currently enrolled student at QMUL 
2. Good knowledge of QMUL's digital learning platforms (QMplus, Q-Review and more.) 
3. Strong communication skills 
4.  Ability to explain technical concepts clearly 
5. Good teamwork skills 
6. Willingness to work collaboratively with other student ambassadors and the TEL Team. 
7. Ability to pick up new technologies in short order. 

Desirable

1. Video editing and production 
2. Media creation 
3. Presentation 

• assisting in conducting research activities related to computer vision, including literature reviews, data collection, experimentation, and analysis
• assisting in the development and implementation of computer vision algorithms, including image processing, object detection, recognition, segmentation, and tracking
• preparing and annotating datasets for training and evaluation purposes, ensuring data quality and relevance to research objectives
contributing to the solution in a form of software tools and frameworks for computer vision research, using programming languages such as Python or C/C++
• assisting in the analysis of qualitative and quantitative data, as directed.

N/a

• Some prior experience and strong interest in the subject of Computer Vision
• Understanding of deep learning frameworks (e.g., TensorFlow Keras, PyTorch) and some proficiency in training convolutional neural networks (CNNs) for computer vision tasks.
• Familiarity in training deep learning models using preprocessed and augmented datasets, monitoring model performance and convergence during training.
• Practical knowledge in utilizing programming languages relevant to machine learning, deep learning and computer vision (Python 3.4 and above is an absolute must).
• Experience working with video / image data, including data preprocessing, annotation and analysis using popular libraries (e.g. OpenCV)
Knowledge of common evaluation metrics for assessing model performance in computer vision tasks, such as accuracy, precision, recall, and F1 score.
•  Knowledge in web frameworks written in Python (e.g. Flask) is desirable but not essential

PhD Students, join us as an Application Adviser (training provided) and make a difference by supporting King's students to succeed with their job applications, starting September 2025.   There will be approximately 4 hours paid training to be completed before September.

Don't rule yourself out!

If you're wondering if you'd be good enough, whether you've got the right background or if you'd fit in please read on. The King's Careers & Employability team is here to support all students and we achieve that by valuing diversity and being inclusive in what we do. We?d like you to be part of that and bring your own lived experience to working with us an Application Adviser! 

What's the job? 
King's Careers & Employability Application Advisers deliver one-to-one advice to students at King's College London on their applications for work (including internships and placements) and/or further study. The support is mainly used by undergraduate and postgraduate taught students seeking advice on CVs, application forms, personal statements and cover letters for both work (including internships and placements) and further study.   
The individual Application Advice sessions are 20 minutes long and run Mondays to Fridays.  Sessions will be delivered predominantly on campus (The Strand and Guys) face to face and (online) using Microsoft Teams. A laptop will be provided. 

Application Advisers usually work with students from any subject. One application adviser will have the chance to support undergraduate students from the Faculty of Natural, Mathematical & Engineering Sciences (NMES) who are applying for placements as part of their course.  We are trailing offering bespoke appointments to meet the needs of international students. 

Who will you work with? 
You will be joining a small team of Application Advisers and you will be trained and supported in your role by the team and the wider King?s Careers & Employability team. You can find out more about the King's Careers & Employability support for students here. 

When will you work?

Hours per week: We expect to be able to offer 7 - 14 hours per week in the Autumn term and 2-5 hours a week in the Spring term.   We are flexible about which days of the week you work, as we realise you'll have other commitments. We'll agree a regular pattern with you and can flex this if you let us know. Start and end dates: early September 2025 through to end March 2026 (term time). We expect there to be more hours available in the Autumn than the Spring.

What will you earn?

18.00 per hour (including training and any management meetings). 

What training and support will you get?
There will be approximately 4 /6 hours of self-paced learning to complete over the Summer. In September Application Advisers will be inducted with 2x2 hour training sessions. The first will be delivered virtually on the afternoon of Monday 1st September 2025, the second will be on in person on the Strand Campus on the afternoon of Thursday 4th September 2025. You will need to be available on these dates.  There will be on-going training and peer review as appropriate as well as regular informal support. 

How to apply 
Please apply through King's Talent Bank  with your CV and cover letter by midnight on Wednesday 30th April 2025. We are particularly interested in hearing about how your commitment to equality and diversity could support students to overcome barriers to progress into work and further study. If you would like an informal discussion about the role before applying, please email careers@kcl.ac.uk and put Application Adviser role in the subject line and one of our team will be in touch. Interviews will take place on campus on Monday 19th May 2025.

Applicants must have:

• Be a PhD student at Kings during the academic year 2025/2026.
• Progressed from undergraduate level by making a successful application for postgraduate study or research or a graduate employment role.

Skills that we?re looking for: 

• Ability to encourage confidence and to help others to learn.
• Ability to explain new ideas and ways of doing things to students in a way that they can understand.
• Ability to adapt the approach you take and way you communicate to suit the student you are supporting.
• Positive and proactive attitude towards your work, and a genuine interest in helping students to learn and develop. 
• Commitment to equality, diversity and inclusion and to supporting students (in particular those from groups under-represented in HE) to overcome barriers to their progress into work or further study.
• Good attention to detail.
• Personal experience of making successful application for postgraduate study or research or a graduate employment role.
• Fluent spoken and written English.