/PhD positon Deep Learning on Time series Data for Health Care

PhD positon Deep Learning on Time series Data for Health Care

Research & development - Gent Zwijnaarde | More than two weeks ago

The proposed PhD research is defined within the context of several national and international collaborations on the application of machine learning to biomedical data. 

Ghent University – SUMOLab - imec IDLab (Ghent University, Belgium)

IDLab is a core research group of imec, a world-leading research and innovation hub in nanoelectronics and digital technologies, with research activities at Ghent University. IDLab performs fundamental and applied research on data science and internet technology, and is, with over 300 researchers, one of the larger research groups at imec. Our major research areas are machine learning and data mining; semantic intelligence; multimedia processing; distributed intelligence for IoT; cloud and big data infrastructures; wireless and fixed networking; electromagnetics, RF & high-speed circuits and systems. 

The activities of SUMO Lab are embedded in this stimulating environment and include predictive analytics, hybrid AI, machine learning, time series analysis, anomaly/event detection, etc., with applications in the health care sector.

What you will do

The omnipresence of sensors causes a growth of data that offers the potential for a significant transformation in the health care sector. As wearable devices are becoming more widespread, continuous measurements of critical biomarkers can be performed to collect longitudinal data. This data can be analyzed using deep learning techniques to facilitate patient screening, support medical diagnosis, and forecast important medical events. Furthermore, by considering the longitudinal aspect of the data, patient health trajectories can be identified that allow the tracking of disease progression over time. Potential application areas include the prediction of heart arrhythmias, such as atrial fibrillation, or the assessment and monitoring of cardiovascular health through analysis of various parameters that are measured with novel hardware devices. An important consideration is the interpretability of the models, which provides clinicians with insights into the reasoning behind predictions, allowing them to validate and trust the model. Another key aspect is the quantification of model uncertainty, which provides a measure of confidence in the models predictions, enabling clinicians to make more informed decisions.

The proposed PhD research is defined within the context of several national and international collaborations on the application of machine learning to biomedical data. You are expected to actively work and significantly contribute to research projects in this area.

What we do for you

We offer the opportunity to do full-time research in an international (with over 17 nationalities at IDLab, part of imec and Ghent University) and friendly working environment, with a competitive salary at Ghent University. While grounded in fundamental academic research, as a PhD candidate you will also participate in collaborative research with industrial and/or academic partners in Flanders and/or on a wider geographic scale (e.g., EU H2020 projects), in the framework of new/ongoing projects. Furthermore, you will publish your research results at major international conferences and in journal papers, as part of meeting the requirements for your PhD. The PhD position is available starting April 2024.

Who you are

Highly creative and motivated PhD student with the following qualifications:

  • You have (or will obtain in the next months) a master degree in Computer Science, or a master degree in Computer Engineering or Biomedical Engineering  with excellent ('honors'-level) grades.
  • You have strong computer science skills (python, C++, etc.).
  •  You have a strong interest in machine learning and biomedical engineering, and are eager to advance the state-of-the-art.
  • Experience with machine learning algorithmic approaches or frameworks (such as PyTorch, Tensorflow, GPFlow, etc.) is considered a significant plus.
  • Experience with analysis of biomedical data (e.g. ECG, MMG, EEG,…) is a significant plus.
  • You are a team player and have strong communication skills.
  • Your English is fluent, both speaking and writing.


Send your application by email or any questions concerning this vacancy to prof. Dirk Deschrijver (dirk.deschrijver@ugent.be) and Prof. Tom Dhaene (tom.dhaene@ugent.be), indicating “Job Application: Deep Learning on Time series Data for Health Care” in the subject.

Applications should include:

  1. an academic / professional resume,
  2. a personal motivation letter,
  3. transcripts of study results,
  4. at least two reference contacts.

After a first screening, selected candidates will be invited for an interview as part of multi-stage selection process.

  • Application deadline: Until the vacancy is filled.
  • Type of contract: Full-time scholarship
  • Employment: Temporary (4 years), with yearly progress evaluation
  • Earliest starting date: April 2024
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