KEY TAKEAWAYS

• 
  Hours
  40 hr.
• 
  Salary indication
  Salary gross/monthly
  based on full-time
  € 2,901 - € 3,707
• 
  Deadline
  31 Jan 2025
  A hip fracture in older adults is associated with complications and a high mortality rate of 10% within one month and 30% within one year after hip fracture surgery. It is therefore crucial to monitor patients’ health condition continuously and accurately after surgery to measure and evaluate patients’ recovery progress, and timely detect and even predict clinical adverse events like delirium, cardiac arrhythmias and pneumonia. In this project, the University of Twente (Biomedical Signals and Systems group) in collaboration with the top clinical hospital Ziekenhuisgroep Twente aims to develop such a health condition monitoring system to assist patients’ recovery management and ultimately reduce the complication and mortality rate and increase their quality of life after hip fracture surgery.
  This PhD position will focus on the health monitoring system development mainly based on multimodal physiological signals, for instance, inertial measurement unit (IMU), electrocardiography (ECG), photoplethysmogram (PPG), Electrodermal activity (EDA), and contactless movement and physiology signals. Specifically, the PhD researcher will develop physiological-model-based artificial intelligence technologies to assess patients’ recovery process and detect or even predict the occurrence of clinical adverse events like delirium, cardiac arrhythmias and pneumonia among the elderly after hip fracture surgery. To obtain relevant data for the above described technology development and its feasibility test, the PhD candidate will also design a medical research experimental protocol for both a healthy control population and a target patient population, and apply for the protocol’s ethical approval. Please check this website for more information about the relevant ethical regulations and approval process in the Netherlands), and take main responsibilities for performing the approved experiment.
  The prospective PhD candidate is expected to perform high quality and internationally visible research with publications in high rank peer-reviewed journals. The candidate will be affiliated to BSS-Ying Wang’s Research Lab and mainly (co-)supervised by dr. Ying Wang, prof. dr. Johannes H. Hegeman and prof. dr. ir. Peter H. Veltink at the Biomedical Signals and Systems group at the University of Twente. The candidate is also expected to closely collaborate with the other partners within the SMARTTEST project. The candidate will be appointed for a period of four years, at the end of which a PhD thesis needs to be delivered. During this period, the PhD candidate will be offered the opportunity to broaden their knowledge by joining MSCA SMARTTEST consortium meetings and by participating in (inter)national conferences and workshops.

YOUR PROFILE

We are looking for highly motivated, enthusiastic and curiosity-driven researchers:

• You have, or are about to get, a master’s degree in biomedical engineering, electrical engineering, technical medicine, or a related field.
• You have a solid background in biomedical signal analysis, physiology dynamic systems, and machine learning technologies, and preferably have experience in designing and performing experiments on human subjects.
• You have strong programming skills, such as, in Matlab\Python.
• You are creative, like to push boundaries and have strong organisational skills in designing, planning and implementing research activities.
• You are highly open-minded and motivated to work on the challenges we are facing in healthcare by developing cutting-edge digital health monitoring technology.
• You are an excellent team player in an enthusiastic and hardworking group of scientists healthcare professionals, engineers, physicians, and working on a joint assignment.
• You are proficient in English and able to collaborate intensively with healthcare professionals as well as with industrial and academic parties in regular meetings and work visits.
• You can do independent research, have excellent writing skills and preferably, have publication skills.
• Specific MSCA eligibility rules.

Please refer the Job description for details