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

We are looking for a research assistant to support us for a short time with a number of projects in the Policy Institute?s Evidence Development and Incubation Team (EDIT). 

The research assistant will be supporting the team with carrying out aspects of the qualitative research. Activities will include tasks such conducting observations, scheduling qualitative interviews, arranging transcription, and maintaining folders and fieldwork logs. The research assistant?s work on qualitative research is likely to include data management in NVivo, conducting qualitative interviews, carrying out qualitative analysis if appropriate, and supporting with report drafting including literature reviews and background sections. 

This specific role is for researchers with previous experience working with young people with SEND (especially autism and learning difficulties). The main activities involve: 

1. Working closely with the project team providing feedback on relevant materials to ensure they are adapted to the target group. 

2. Conducting observations during site selection days, surveys (when required) 

3. Conducting semi-structured interviews 

4. Other activities related to the research project, as defined by the Project Manager/Leads

There are 148 hours available for this role. 

• MA/MSc

-Experience working with young people with SEND 

-Understanding of qualitative research approaches 

-Experience conducting semi-structured interviews and observations 

-Experience working as part of a team or in a co-ordination role 

-Experience in carrying out qualitative data management in NVivo 

Desirable:

-Experience conducting qualitative analysis 

-Experiencing with drafting policy reports