PhD on Development of Smart Algorithms for Context-Aware Patient Monitoring Hiring in processFinished, not possible to apply

Introduction

We are seeking a highly motivated and talented PhD candidate to join the SmartNudges project a cutting-edge initiative aimed at revolutionizing patient monitoring in clinical settings. The focus of this PhD research is to develop optimal methods for capturing and sampling patient states with a primary emphasis on designing smart algorithms to trigger non-invasive blood pressure (NIBP) measurements at critical times. This will involve leveraging physiological sensor signals such as the electrocardiogram (ECG) and photoplethysmogram (PPG) to create context-aware adaptive monitoring solutions. The research will be conducted in collaboration with Philips and the Catharina Ziekenhuis (CZE).

Job Description

Key Responsibilities:

• Develop a generalizable and explainable (gray-box) model for adaptive patient monitoring.
• Utilize a mixed approach combining real and synthetic data for algorithm development.
• Investigate and implement optimum sampling strategies including sparse and compressed sampling techniques.
• Explore the applicability of neural networks in clinical workflows ensuring solutions are practical and scalable.
• Design and build a technology demonstrator prototype of clinical-testing grade.
• Collaborate with interdisciplinary teams including clinicians engineers and machine learning (ML) and artificial intelligence (AI) researchers.
• Publish findings in high-impact journals and present at international conferences.

Expected Outcomes:

• A partially explainable AI model for context-aware NIBP measurement triggering.
• A validated prototype ready for clinical testing.
• Contributions to the scientific understanding of ML / AI-based adaptive context-aware monitoring for triggering vital sign measurements in general.

Job Requirements

• Masters degree in Biomedical Engineering Electrical Engineering Computer Science or a related field.
• Strong foundation in biomedical signal processing and hands-on experience with clinical data.
• Knowledge of information theory sampling theorems and optimum sampling strategies.
• Proficiency in machine learning deep learning and artificial intelligence techniques.
• Familiarity with clinical applications and workflows.
• Basic understanding of statistics.
• Programming expertise in Python or similar languages with experience in machine learning frameworks (e.g. TensorFlow PyTorch Scikit-learn).
• Excellent communication skills in English both written and oral.

Preferred Skills:

• Affinity for understanding human physiology and clinical environments.
• Experience with wearable sensor data and multimodal datasets.
• Ability to work in interdisciplinary teams and adapt to dynamic research environments.
  
  

Conditions of Employment

A meaningful job in a dynamic and ambitious university in an interdisciplinary setting and within an international network. You will work on a beautiful green campus within walking distance of the central train addition we offer you:

• Full-time employment for four years with an intermediate assessment after nine months. You will spend a minimum of 10% of your four-year employment on teaching tasks with a maximum of 15% per year of your employment.
• Salary and benefits (such as a pension scheme paid pregnancy and maternity leave partially paid parental leave) in accordance with the Collective Labour Agreement for Dutch Universities scale P (min. 3059 - max. 3881).
• A year-end bonus of 8.3% and annual vacation pay of 8%.
• High-quality training programs and other support to grow into a self-aware autonomous scientific researcher. At TU/e we challenge you to take charge of your own learning process.
• An excellent technical infrastructure on-campus childrens day care and sports facilities.
• An allowance for commuting working from home and internet costs.
• A Staff Immigration Team and a tax compensation scheme (the 30% facility) for international candidates.

About us

Eindhoven University of Technology is a leading international university within the Brainport region where scientific curiosity meets a hands-on mindset. We work in an open and collaborative way with high-tech industries to tackle complex societal challenges. Our responsible and respectful approach ensures impact today and in the future. TU/e is home to over 13000 students and more than 7000 staff forming a diverse and vibrant academic community.

The mission of the Department of Electrical Engineering is to acquire share and transfer knowledge and understanding in the whole field of Electrical Engineering through education research and valorization. We work towards a Smart Sustainable Society a Connected World and a healthy humanity (Care & Cure). Activities share an application-oriented character a high degree of complexity and a large synergy between multiple facets of the field.

Research is carried out into the applications of electromagnetic phenomena in all forms of energy conversion telecommunication and electrical signal processing. Existing and new electrical components and systems are analyzed designed and built. The Electrical Engineering department takes its inspiration from contacts with high-tech industry in the direct surrounding region and beyond.

The department is innovative and has international ambitions and partnerships. The result is a challenging and inspiring setting in which socially relevant issues are addressed.

Information

Do you recognize yourself in this profile and would you like to know more Please contact the hiring manager Simona Turco Assistant Professor .

Visit our website for more information about the application process or the conditions of employment. You can also contact .

Curious to hear more about what its like as a PhD candidate at TU/e Please view the video.

Are you inspired and would like to know more about working at TU/e Please visit our career page.

Application

We invite you to submit a complete application by using the apply button. The application should include a:

• Cover letter in which you describe your motivation and qualifications for the position.
• Curriculum vitae including a list of your publications and the contact information of three references. Kindly note that we may reach out to references at any stage of the recruitment process. We recommend notifying your references upon submitting your application.

Ensure that you submit all the requested application documents. We give priority to complete applications.

We look forward to receiving your application and will screen it as soon as possible. The vacancy will remain open until the position is filled.

Please note

• You can apply online. We will not process applications sent by email and/or post.
• A pre-employment screening (e.g. knowledge security check) can be part of the selection procedure. For more information on the knowledge security check please consult the National Knowledge Security Guidelines.
• Please do not contact us for unsolicited services.