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Research Assistant

 

Job Description

Research Assistant – sample size investigation for clinical texts classification using NLP



A team in BHI is looking for a motivated research assistant to work on a project investigating optimal sample size for Natural Language Processing (NLP) classification tasks that require manual annotations. The tasks involve:



·       running simulations using deep learning models to investigate model performances in various language settings and training corpora sizes;



·       developing a GitHub project page and a well-documented code;



·       participating in dissemination activities (e.g. preparing and participating in an interactive online seminar).



A successful candidate can start as soon as possible and work till the end of July, in a collaboration with myself, Angus Roberts, Jaya Chaturvedi, and Daniel Stahl. The hours (14h/week) can be worked as two full days or spread over the week, remotely or in the office (Denmark Hill). Please write to diana.shamsutdinova@kcl.ac.uk to express your interest.



Project Description: Natural Language Processing methods are widely applied to extract information from clinical texts and present it in a structured way. However, unlike in statistical data analyses, there are no methods available for estimating the sample size needed. Our project aims to assess optimal sample size for the development of clinical NLP models and how these requirements change depending on the documents and language properties. By taking a simulation approach and following modern guidance on model validation, we will be able to investigate model performances in various scenarios and provide guidance on sample sizes for clinical NLP tasks.



Qualifications

The role is suitable for a current MSc/PhD student/postdoc/early career researcher in Computer science, Engineering, Health Informatics, Statistics, or a related field.



Skills

·       Strong analytical skills;



·       Knowledge of Python programming language;



·       Understanding model validation techniques such as cross-validation and evaluation metrics such as AUC-ROC/sensitivity/specificity/precision, 



·       Ability to work independently and in a team.

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I want support with developing a protortype for an app that can help record people entering and leaving a room. This will be used using the developed app which will be connected to an NFC tag to record who has entered a lab space, similar to the solution provided here



- Develop the app



- Connect it to an NFC tag



- Develop reporting mechnism



Qualifications

A qualification or reelvant expecrience in IT, primarily app devleopment



Skills

- App development, primrily trhough MS Power apps



- System development nderstanding



- Experience using Microsoft 365 suite




  •     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

“Beyond 1932” is an ERC/UKRI research project based at King’s Music Department under the lead of Professor Martin Stokes which explores the sonic legacy of the 1932 Arab Music Congress. The Beyond 1932 team is looking for a student with website design experience (specifically Wordpress experience) to help design and create a dynamic, interactive website for the project. The job will involve initial meeting(s) with the team to discuss our requirements; creating the Wordpress website and populating it with content we provide; progress meetings with the team to discuss changes; creating subsequent draft(s) of the website.



We anticipate the job will be approximately 15-30 hours in total, and will need to be completed in June 2024.



Payment is £18.07 per hour and timesheets will be submitted via King’s Talent Bank. Registration to King’s Talent bank is necessary to apply for this role.



Please note this job is only open to current KCL students and KCL alumni (not external candidates). 



If you are interested in applying, please email Sophie Frankford at sophie.frankford@kcl.ac.uk with a paragraph outlining your experience and motivation to get involved, and a link to any examples of your previous website design work. The deadline for applications is 5pm, 25th May 2024.



 



 



Qualifications

N/A



Skills

Essential criteria




  • Experience with Wordpress website design

  • Ability to work as part of a team and communicate clearly



 



Desirable criteria




  • Arabic language proficiency 

  • An interest in music of the Middle East and North Africa 

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