IT / Web / Telecomms

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.

• A background in Informatics or Computer Science is required, with higher education qualifications being an advantage.

• 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)

• 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