荷语区鲁汶大学

Machine-learning Modelling of Cardiorespiratory Fitness

项目介绍

The Research Unit Hypertension and Cardiovascular Epidemiology at KU Leuven specializes in epidemiology and pathophysiological mechanisms of cardiovascular diseases and risk factors. We have a long-standing experience in organizing and coordinating epidemiological studies, in collecting standardized, high-fidelity cardiovascular phenotypes, clinical exercise tests, and in statistical analysis.

Project

Clinical exercise tests could improve the personalized risk profiling and management of cardiovascular disease. Yet, current practice only considers a limited selection of cardiopulmonary exercise indexes in isolation. To utilize the full value of clinical exercise testing data, this PhD project aims to apply advanced machine learning approaches on tabular and time-series data that has been collected/will be collected in patients and general population. The candidate will work on developing integrative models that characterize personalized cardiorespiratory fitness profiling and its relation to subclinical stages of heart failure. These models will be further validated in external patient cohorts. The candidate will work in close collaboration with epidemiological,cardiac rehabilitation and computer science teams, conducting applied research in the machine learning domain.

Profile

  • You have a master degree in computer science, informatics, artificial intelligence, or equivalent, with excellent (‘honors’-level) grades.
  • You have followed courses related to data mining or machine learning.
  • You have a passion for data science and demonstrable machine learning skills (preferably in the medical domain). Be sure to mention any knowledge of, or previous experience with machine learning or risk predictor development.
  • You are an experienced programmer in Python. Familiarity with other languages such as R and software engineering skills will be considered an asset. Please, mention examples of your open-source code (e.g. a link to a GitHub repository).
  • You have a strong interest in applying machine learning models in medicine; you are motivated, hard-working, and creative.
  • You have excellent oral and written communication skills in English.
  • You are able to communicate about your work at local and international congresses and to people from another disciplines.

Offer

We offer full-time employment for a PhD researcher. Starting date is from October, 2021. The appointment will be for 1 year initially and will be extended after a positive evaluation. The candidate will be working at the Campus Sint Rafaël, in Leuven, with regular interactions with leading centers in machine learning at KU Leuven. (S)he will enter the doctoral Health and Technology program of the KU Leuven Doctoral School of Biomedical Sciences.

Interested?

To apply forthis position, please send your CV and a cover letter by email toProf. dr. Tatiana Kouznetsova,Research Unit Hypertension and Cardiovascular Epidemiology, KU LeuvenDepartment of Cardiovascular Sciences, Campus Sint Rafaël, Kapucijnenvoer 35, Block H, Box 7001, B-3000 Leuven, Belgium. Email: tatiana.kouznetsova@kuleuven.beYou can apply for this job no later than July 30, 2021 via the online application toolKU Leuven seeks to foster an environment where all talents can flourish, regardless of gender, age, cultural background, nationality or impairments. If you have any questions relating to accessibility or support, please contact us at diversiteit.HR@kuleuven.be.

录取要求

  • You have a master degree in computer science, informatics, artificial intelligence, or equivalent, with excellent (‘honors’-level) grades.
  • You have followed courses related to data mining or machine learning.
  • You have a passion for data science and demonstrable machine learning skills (preferably in the medical domain). Be sure to mention any knowledge of, or previous experience with machine learning or risk predictor development.
  • You are an experienced programmer in Python. Familiarity with other languages such as R and software engineering skills will be considered an asset. Please, mention examples of your open-source code (e.g. a link to a GitHub repository).
  • You have a strong interest in applying machine learning models in medicine; you are motivated, hard-working, and creative.
  • You have excellent oral and written communication skills in English.
  • You are able to communicate about your work at local and international congresses and to people from another disciplines.

项目概览

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欧陆, 比利时 所在地点
带薪项目 项目类别
截止日期 2021-07-30
荷语区鲁汶大学

院校简介

鲁汶大学是比利时久负盛名的世界百强名校。
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联系方式

电话: +32 16 324010

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