An Artificial Intelligence based approach for the Classification of Pediatric Heart Murmurs and Disease Diagnosis using Wireless Phonocardiography( WD_2023_70_SPONS)

An Artificial Intelligence based approach for the Classification of Pediatric Heart Murmurs and Disease Diagnosis using Wireless Phonocardiography( WD_2023_70_SPONS)

Deadline: 22 May 2024

Research Field:  Professions and applied sciences

Funding Type: Funding
More Information: https://www.scientifyresearch.org/grant/career-development-award-basic-biological-science-italy/

Project Key Words: Congenital heart disease, phonocardiogram, Artificial Intelligence

Post summary

Our project focuses on harnessing the power of Artificial Intelligence (AI) to analyze phonocardiogram (PCG) data for the early detection of congenital heart disease (CHD). By developing advanced AI algorithms, we aim to revolutionize the way CHD is diagnosed and managed, leading to better outcomes for patients.

Person specification

Qualifications

Essential

  • Honours Degree (minimum 2:1) in biomedical engineering, computer science, electrical/ electronics engineering, or a related field.
  • Strong background in signal processing and machine learning.

Desirable

  • Proficiency in programming languages such as Python, R or MATLAB.
  • Practical experience in simulation environments and Machine Learning libraries.
  • Experience with cardiovascular physiology or cardiology research.
  • Experience with GUI development and web applications.

 

Knowledge & Experience

 Essential

  • Experience with machine learning techniques, including deep learning and neural networks.
  • Strong analytical and problem solving skills.
     

 Desirable

  • Previous research experience in healthcare or medical signal processing projects.
  • Experience with data visualization tools.
  • Familiarity with phonocardiogram data analysis and interpretation.

 

Skills & Competencies

Essential

  • Applicants whose first language is not English must demonstrate on application that they meet SETU’s English language requirements and provide all necessary documentation. See Page 7 of the Code of Practice
  • In order to be shortlisted for interview, you must meet the SETU English speaking requirements so please provide evidence in your application.  
     

Desirable

  • Excellent written and verbal communication skills.
  • Willingness and motivation to learn and experience new theoretical and technological areas.

 

May 4, 2024 at 11:13 AM