Offer Description
Last application date Dec 31, 2024 00:00
Department TW05 – Department of Information Technology
Contract Limited duration
Degree master degree in Computer Science, or a master degree in Computer Engineering or Biomedical Engineering
Occupancy rate 100%
Vacancy type Research staff
Job description
Vacancy: PhD position
Deep Learning on Time series Data for Health Care
ABOUT GHENT UNIVERSITY
Ghent University is a world of its own. Employing more than 15.000 people, it is actively involved in education and research, management and administration, as well as technical and social service provision on a daily basis. It is one of the largest, most exciting employers in the area and offers great career opportunities.
With its 11 faculties and more than 85 departments offering state-of-the-art study programmes grounded in research in a wide range of academic fields, Ghent University is a logical choice for its staff and students.
SUMOLab – 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.
Job Description
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.
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Send your application by email or any questions concerning this vacancy to prof. Dirk Deschrijver ([email protected] ) and Prof. Tom Dhaene ([email protected] ), 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, and (3) transcripts of study results, and (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.
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STATUS: EXPIRED
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