荷语区鲁汶大学

PhD position in explainable machine learning for personalized patient follow-up

项目介绍

Itec is a research group at KU Leuven and imec, Flanders’ high-tech research and innovation hub for nanoelectronics and digital technologies. On the campus Kortrijk of the KU Leuven, the group conducts interdisciplinary research on the design, development and evaluation of personalized and adaptive digital solutions. Itec’s primary application domains include education, training and health.
The main focus of the AI and machine learning subgroup is to develop new machine learning algorithms to advance the application domains, especially healthcare. In particular, we focus on supervised, unsupervised and semi-supervised learning. Key activities in the group relate to multi-label/target prediction, recommender systems, active learning, ensemble learning, survival analysis and longitudinal data analysis; always with a specific attention to explainability.

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Project

This PhD position, which is funded by the Research Foundation Flanders (FWO), consists of two main parts. First, the candidate will develop machine learning models aimed at improving the follow-up of neurocognitive function in critically ill children after discharge from the intensive care unit. This project involves developing personalized test sequences to enhance assessment efficiency and predicting potential adverse consequences to facilitate preventive strategies. This will involve working with real data (including its challenges, such as data preprocessing, dealing with missing data, etc.) from and in consultation with our university hospital’s intensive care unit. Second, in order to solve the first part, the candidate will carry out fundamental research on the topics of multi-label learning, semi-supervised learning and label ranking. The candidate will develop new explainable algorithms for these tasks, and as such also make contributions to the machine learning domain. Note that the data structure the candidate is expected to work on is mostly tabular data (rather than text or images, for example).
Besides doing research, the candidate is expected to participate in educational activities (participate in seminars, be involved in teaching, exam surveillance, …).

Profile

  • You have a master’s degree in computer science, data science, informatics, statistics, artificial intelligence, (mathematical) engineering, or equivalent, with excellent (‘honors’-level) grades. Candidates expecting to graduate in summer 2025 are also welcome to apply, they should demonstrate their excellent results via their academic transcript.
  • You have followed fundamental courses related to machine learning, and show a significant enthusiasm for, and knowledge of, this domain. Be sure to mention in your motivation letter any knowledge of (or previous experience with) the machine learning research topics of the PhD project as detailed in the project description above.
  • You are an experienced programmer in Python.
  • You have a strong interest in working on real healthcare applications and in interacting with healthcare professionals. You treat the medical data and the associated research questions with the necessary respect. Be sure to mention in your motivation letter any previous experience with healthcare projects in general, and any background in working with critical care data in particular.
  • You are motivated, curious and creative. You are able to communicate about your work to people from another discipline.
  • You are able to work independently, but also to integrate and interact with a team of fellow PhD researchers and postdocs in our research group.
  • You have excellent oral and written communication skills in English. Knowledge of Dutch will be considered an asset. 

Offer

We offer full-time employment for a PhD researcher. The appointment will be for 1 year initially and will be extended after positive evaluation.
The candidate will be working at KU Leuven Campus Kulak in Kortrijk. (S)he will enter the doctoral program of the KU Leuven Doctoral School of Biomedical Sciences.
As a PhD student, you will have every opportunity to develop yourself further in your professional career, by studying literature, attending seminars and workshops, participating in international conferences and interacting with leading researchers from multiple disciplines.
The position offers flexibility and the opportunity to work in an enthusiastic team in a stimulating multicultural environment. Your research will contribute to developments in healthcare that have a high societal impact.
In addition to a competitive scholarship, KU Leuven also offers several additional benefits, such as hospitalization insurance, eco-vouchers, reimbursement of commuting expenses by public transport, inexpensive meals, a KU Leuven bicycle, …

Interested?

For more information please contact Prof. dr. Celine Vens, tel.: +32 56 24 64 98, mail: celine.vens@kuleuven.be.
No applications via e-mail, please use the KU Leuven online application tool.  Applications via e-mail will not be accepted.You can apply for this job no later than April 13, 2025 via the online application tool

KU Leuven strives for an inclusive, respectful and socially safe environment. We embrace diversity among individuals and groups as an asset. Open dialogue and differences in perspective are essential for an ambitious research and educational environment. In our commitment to equal opportunity, we recognize the consequences of historical inequalities. We do not accept any form of discrimination based on, but not limited to, gender identity and expression, sexual orientation, age, ethnic or national background, skin colour, religious and philosophical diversity, neurodivergence, employment disability, health, or socioeconomic status. For questions about accessibility or support offered, we are happy to assist you at this email address.

Heb je een vraag over de online sollicitatieprocedure? Raadpleeg onze veelgestelde vragen of stuur een e-mail naar solliciteren@kuleuven.be

项目概览

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欧洲, 比利时 所在地点
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截止日期 2025-04-13
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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