PhD scholarship in Advanced Machine Learning for Critical Events Modelling and Detection for High-Risk Patients

Updated: 6 months ago
Deadline: The position may have been removed or expired!

Are you interested in contributing to save risk patients from life threatening complications using advance methods in machine learning, and biomedical signal processing?

DTU Health Tech invites applicants for a 3-years PhD scholarship as part of the Wireless Assessment of Respiratory and circulatory Distress (WARD) project supported by the Danish Innovation Foundation. WARD aims at designing and implementing a novel and fully automatic clinical support system for major surgery patients and acute medical disease patients, which potentially will be used by all major university hospitals in Denmark.

As a member of the WARD research project team you will contribute in defining and developing next generation monitoring and interpretation clinical support system for highly reducing serious complications for high-risk patients.

Miniature devices on each patient will measure the most important physiological events, and there is a need for inventing biomedical signal processing of modalities and advanced machine learning for robust interpretation of abnormal micro- and macro events and diseases states. Focus on design of feature fusion and decision fusion in connection with advanced machine learning will be important to ensure robust estimation of complications in high-risk patients.

Efficient interdisciplinary research between technical and medical experts is the key to success, because the fully automatic clinical support system can only be realized based on intelligent machine learning modelling of uniquely defined medical modelling and annotation of critical events.

Responsibilities and tasks
The successful candidate will focus on: 

  • Design and implementation of machine learning algorithms to discover critical events in the measured modalities
  • Design and application of novel biomedical signal processing algorithms and advanced machine learning methods for real-time interpretation of critical events in signals from body-worn “wear-and-forget” devices from multiple subjects
  • Contributing to highly interdisciplinary collaboration between engineers, medical doctors, technical PhDs, Postdocs, medical PhDs on development and evaluation of the clinical support system
  • Contributing to clinical support system design, implementation and evaluation
  • Writing scientific journal papers


  • Master degree in biomedical engineering or electrical engineering, biomedical data science or equivalent qualification with preferably publication record
  • Excellent skills in advanced biomedical signal processing methods
  • Excellent skills in advanced machine learning methods
  • Strong programming experience preferably in Matlab, Python, and C++
  • Interest in real-time computing for multiple subjects
  • Collaborative skills, especially with research management team
  • Experienced in command of English (written and spoken) as well as technical writing.
  • An understanding of advanced mathematical & statistical principles behind current best practices in high-throughput data analysis.
  • Ability to work both independently and collaboratively in interdisciplinary organizations (technical/medical), and to handle concurrent projects.
  • Enthusiasm for continued education.

Approval and Enrolment
The scholarship for the PhD degree is subject to academic approval, and the candidate will be enrolled in one of the general degree programmes at DTU. For information about our enrolment requirements and the general planning of the PhD study programme, please see the DTU PhD Guide .

The assessment of the applicants will be made by the research management team: Assoc. Professor Helge B.D. Sørensen DTU Health Tech/chairman, Assoc. Professor Eske K. Aasvang, Rigshospitalet, University of Copenhagen, and Assoc. Professor Christian S. Meyhoff, Bispebjerg-Frederiksberg University Hospital, University of Copenhagen.

We offer
DTU is a leading technical university globally recognized for the excellence of its research, education, innovation and scientific advice. We offer a rewarding and challenging job in an international environment. We strive for academic excellence in an environment characterized by collegial respect and academic freedom tempered by responsibility.

Salary and appointment terms
The appointment will be based on the collective agreement with the Danish Confederation of Professional Associations. The allowance will be agreed upon with the relevant union. The period of employment is 3 years.


  • Department of Health Technology, Technical University of Denmark (main site)
  • Rigshospitalet and Bispebjerg-Frederiksberg Hospital

You can read more about career paths at DTU here .

Further information
Further information may be obtained from Assoc. Professor Ph.D. Helge B.D. Sørensen, , Digital Health.

You can read more about the Department of Health Technology on .

Application procedure
Please submit your online application no later than 20 August 20 2019 (24:00 hours local time). Note:  PhD scholarship start date October 1 2019.

Applications must be submitted as
one PDF file containing all materials to be given consideration. To apply, please open the link "Apply online", fill out the online application form, and attach all your materials in English in one PDF file. The file must include: 

  • A letter motivating the application (cover letter)
  • Curriculum vitae
  • Grade transcripts and BSc/MSc diploma
  • Excel sheet with translation of grades to the Danish grading system (see guidelines and Excel spreadsheet here )

Candidates may apply prior to obtaining their master's degree but cannot begin before having received it.

Applications and enclosures received after the deadline will not be considered.

All interested candidates irrespective of age, gender, disability, race, religion or ethnic background are encouraged to apply.

DTU Health Tech engages in research, education, and innovation base on technical and natural science for the healthcare sector. The Healthcare sector is a globally expanding market with demands for the most advanced technological solutions. DTU Health Tech creates the foundation for companies to develop new and innovative services and products which benefit people and create value for society. DTU Health Techs expertise spans from imaging and biosensor techniques, across digital health and biological modelling, to biopharma technologies.

DTU is a technical university providing internationally leading research, education, innovation and scientific advice. Our staff of 6,000 advance science and technology to create innovative solutions that meet the demands of society, and our 11,200 students are being educated to address the technological challenges of the future. DTU is an independent academic university collaborating globally with business, industry, government and public agencies.  

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