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.
Qualifications
N/a
Skills
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'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
Help create online self-paced training courses for new teaching staff
Assist in developing in-person induction sessions for new teaching staff
Participate in creating student case study videos
Share your experience with digital learning tools at QMUL
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
We are seeking a Research Assistant with expertise in web development and implementation to support the enhancement of a digital resource currently under development. This resource, based on cutting-edge linguistic research, focuses on motion verbs in Latin and Ancient Greek, making complex linguistic structures more accessible and engaging for secondary school students and teachers. The role involves refining and optimizing the existing platform, ensuring a user-friendly experience, and integrating additional linguistic data.
This is an exciting opportunity to contribute to a meaningful educational and research-driven project that connects classical languages with digital innovation.
Please note that compensation includes payment for regular remote meetings.
Qualifications
A background in Informatics or Computer Science is required, with higher education qualifications being an advantage.
Skills
Proficiency in JavaScript and Python
Experience with web development and digital tools for education
Strong problem-solving skills and ability to work independently
Interest in linguistics, digital humanities, or educational technology (preferred but not required)
We have a fantastic opportunity for a Tissue Bank Technician to provide technical support to the Pancreatic Cancer Research Fund Tissue Bank (PCRFTB), to enable comprehensive, efficient and effective service to internal and external researchers. In particular, sample processing, quality control, management of PCRFTB samples, general house-keeping and stock taking.
This is a full time position for a duration of 3 months. We will be paying the successful candidate between ?17.97 - ?21.62 per hour plus holiday pay depending on experience.
Qualifications
First Degree in biological sciences
Minimum of 2 A Levels in relevant subjects (e.g. Biology, Chemistry)
Skills
Working knowledge of Health and Safety, COSHH and GCP regulations and an understanding of the implications of compliance with the Human Tissue Act (HTA)
Knowledge of laboratory health and safety procedures
Experience in handling and processing human tissue in an oncology research environment
Experience of sample archiving and management using LIMS
Experience of managing databases to identify sample cohorts
Experience in nucleic acid extraction
Strong organisational skills and attention to detail
Ability to follow written and oral instructions
Ability to organise own workload and respond to changing priorities
Experience of using Microsoft Office packages (Word, Excel, Outlook and Powerpoint)
Ability to work both independently and as a supportive member of a team
Excellent written and verbal communication
Ability to maintain accurate and complete records
Ability to improve processes
Other
Friendly, positive and professional disposition to establish and maintain effective working relationship with others
Willingness to work flexibly in order to achieve project demands
Self-motivated and able to work without close supervision
Organised and methodical, and able to use own initiative where appropriate
Ability to maintain confidentiality when handling sensitive data
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
Help create online self-paced training courses for new teaching staff
Assist in developing in-person induction sessions for new teaching staff
Participate in creating student case study videos
Share your experience with digital learning tools at QMUL
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
We are seeking a Research Assistant with expertise in web development and implementation to support the enhancement of a digital resource currently under development. This resource, based on cutting-edge linguistic research, focuses on motion verbs in Latin and Ancient Greek, making complex linguistic structures more accessible and engaging for secondary school students and teachers. The role involves refining and optimizing the existing platform, ensuring a user-friendly experience, and integrating additional linguistic data.
This is an exciting opportunity to contribute to a meaningful educational and research-driven project that connects classical languages with digital innovation.
Please note that compensation includes payment for regular remote meetings.
Qualifications
A background in Informatics or Computer Science is required, with higher education qualifications being an advantage.
Skills
Proficiency in JavaScript and Python
Experience with web development and digital tools for education
Strong problem-solving skills and ability to work independently
Interest in linguistics, digital humanities, or educational technology (preferred but not required)
We have a fantastic opportunity for a Tissue Bank Technician to provide technical support to the Pancreatic Cancer Research Fund Tissue Bank (PCRFTB), to enable comprehensive, efficient and effective service to internal and external researchers. In particular, sample processing, quality control, management of PCRFTB samples, general house-keeping and stock taking.
This is a full time position for a duration of 3 months. We will be paying the successful candidate between ?17.97 - ?21.62 per hour plus holiday pay depending on experience.
Qualifications
First Degree in biological sciences
Minimum of 2 A Levels in relevant subjects (e.g. Biology, Chemistry)
Skills
Working knowledge of Health and Safety, COSHH and GCP regulations and an understanding of the implications of compliance with the Human Tissue Act (HTA)
Knowledge of laboratory health and safety procedures
Experience in handling and processing human tissue in an oncology research environment
Experience of sample archiving and management using LIMS
Experience of managing databases to identify sample cohorts
Experience in nucleic acid extraction
Strong organisational skills and attention to detail
Ability to follow written and oral instructions
Ability to organise own workload and respond to changing priorities
Experience of using Microsoft Office packages (Word, Excel, Outlook and Powerpoint)
Ability to work both independently and as a supportive member of a team
Excellent written and verbal communication
Ability to maintain accurate and complete records
Ability to improve processes
Other
Friendly, positive and professional disposition to establish and maintain effective working relationship with others
Willingness to work flexibly in order to achieve project demands
Self-motivated and able to work without close supervision
Organised and methodical, and able to use own initiative where appropriate
Ability to maintain confidentiality when handling sensitive data
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