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IT Engineer

£21,255 - £21,255
 

Job Description

Main duties associated with this post are:   




  • Software installation and configuration  




  • Operating system image deployment  

  • Troubleshooting software installations  

  • IT record keeping and asset management.  

  • Respond to user requests via the school helpdesk. 

  • Support users both onsite and users working remotely. 




  • Provide IT technical support for events. 

  • PC hardware maintenance and upgrades.  

  • Automation using SharePoint Online and MS Office 365 low-code approach 

  • Lifting and moving of equipment e.g. system units, computer monitors and printers.  

  • Carry out any other duties which are appropriate to the post as may be reasonably requested by the supervisor.  



Qualifications

At least 1 of the following :



CompTIA Security+ qualifications or Microsoft Fundamental qualifications (SC-900, AZ-900, etc)



Also..




  • Currently registered students at Queen’s University, Belfast entering pre-final year of an Undergraduate course of study in MEng/BSc Computer Science, MEng/BEng Software Engineering/Software and Electronic Systems Engineering, MSc Applied Cyber Security with professional internship, BSc Computing and Information Technology/Business Information Technology.  

  • 50% average to date in all modules taken to date. 

  • All students for whom English is not their first language must have achieved a minimum pass mark of 7.0 in the writing and speaking band of IELTS (International English Language Test Score) or equivalent. Please note a copy of your IELTS results will be requested by email to your QUB email address following submission of your application). 

  • Understand Windows Networked environment and know how to configure network settings on a windows machine. 

  • Experience of upgrading or maintaining PC hardware.   

  • Experience of installing software or operating systems. 



Skills

  • Understand Windows Networked environment and know how to configure network settings on a windows machine, install and troubleshoot

  • Understand Linux environment (Ubuntu etc)

  • Experience of upgrading or maintaining PC hardware.   

  • Experience of installing software or operating systems. 

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About the Role:

We are seeking a highly motivated Research Assistant to contribute to the development of a medical timeline builder using Large Language Models (LLMs). This project aims to extract and organize temporal information from clinical narratives to construct structured medical timelines that enhance clinical decision-making and patient care. The successful candidate will work at the intersection of natural language processing (NLP), clinical informatics, and AI-driven healthcare applications.

Key Responsibilities:

  • Data Processing & Annotation: Preprocess and structure clinical text datasets (e.g., i2b2, MIMIC) for training and evaluation.
  • LLM Fine-Tuning & Evaluation: Fine-tune state-of-the-art LLMs for temporal information extraction and reasoning in clinical texts.
  • Pipeline Development: Develop and implement a two-stage LLM-based framework for extracting temporal references and constructing medical timelines.
  • Model Benchmarking: Design benchmark datasets and evaluate models on clinical temporal reasoning tasks.
  • Visualization & Integration: Assist in integrating timeline generation results into interactive visualization toolsfor clinical use.
  • Collaboration & Dissemination: Work closely with interdisciplinary teams, including clinicians and AI researchers, and contribute to publications and conference presentations.


Qualifications

Education: Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Biomedical Informatics, or a related field.



Skills
  • Programming Skills: Proficiency in Python, with experience in NLP libraries (e.g., Hugging Face Transformers, spaCy, NLTK).
  • Machine Learning & LLMs: Understanding of deep learning, LLM fine-tuning, and model evaluation techniques.
  • Clinical NLP Experience: Familiarity with medical text processing, clinical terminologies (e.g., SNOMED, UMLS), and temporal reasoning in healthcare.
  • Data Handling: Experience working with structured and unstructured clinical datasets (e.g., i2b2, MIMIC-III).
  • Research & Communication: Strong analytical skills, ability to conduct literature reviews, and contribute to academic writing.
  • 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

    ?    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

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