EngD position within our NewLife project

Functieomschrijving

Are you interested in developing fundamental knowledge in signal processing to push the frontiers of pregnancy monitoring? Do you enjoy technical challenges connected to real clinical and industrial environment? This stimulating EngD position might be the right one for you!

The Biomedical Diagnostic (BM/d) Lab at the Eindhoven University of Technology (TU/e) is seeking an outstanding EngD candidate to work in the field of electrophysiological monitoring of pregnancy with focus on the coupling between mother and fetus. The project is embedded within the European KDT project NewLife in collaboration, among others, with Dutch companies such as Sencure and Philips.

Project description

Over 1 in 5 pregnancies in the developed countries are complicated and considered at high-risk, and this number is expected to increase as a result of the progressive trend to postpone childbirth. Key risks include imminent preterm birth, intra-uterine growth restriction, and fetal asphyxia. When pregnancy complications occur, timely intervention is crucial, but hampered by current diagnostics based on cardiotocography (CTG), which measures fetal heart rate and uterine contractions by a combination of ultrasound Doppler and surface strain measurements using a belt surrounding the abdomen. While Doppler requires user interaction for repositioning the ultrasound probe because of signal loss, the measurement of uterine contractions is inaccurate and cannot assess contraction intensity. In this project, we will introduce a new patch device integrating ultrasound and electrophysiological measurements to substitute current CTG diagnostics with a solution that is more accurate and does not require user interaction.

This EngD project will specifically focus on multichannel electrophysiological measurements aiming at extracting simultaneously the fetal and maternal heart rate, with the aim of characterizing the diagnostic value of their coupling. To this end, algorithms for robust and reliable extraction of the fetal ECG will be developed, along with connectivity and synchronicity measures for the assessment of the coupling between maternal and fetal heart rate and heart rate variability.

Eventually, the availability of multimodal measurements by ultrasound quantifications will favor the development of a robust solution for pregnancy monitoring that exploits redundancy across the measurements.

During your EngD, next to following dedicated courses for technical and professional formation, you will work on the conceptualization and design of the algorithms for extraction of the fetal and maternal heart rate from multichannel electrophysiological recordings, as well as on the design and implementation of reliable measures of coupling between these signals. Machine learning and blind-source separation methods will be employed to boost the algorithm performance, and proper statistical tools will be employed for assessment of the produced outputs. Both detection and classification accuracy will properly and extensively be tested.

Your task will be:

• Study the state-of-the-art algorithms for electrophysiological monitoring of the fetal heart rate, largely available in house, as well as the state-of-the-art metrics to assess connectivity and synchronicity among signals.
• Develop a good understanding of the practical aspects related to the intended clinical application and employed acquisition hardware.
• Design and implement an algorithm for simultaneous fetal and maternal heart rate detection that is adjusted and optimized to the hardware made available for the project by Sencure.
• Design and implement proper metrics to assess the coupling between fetal and maternal heart rate and heart-rate variability.
• Possibly design and implement denoising strategies that exploit the availability of multimodal recordings (ultrasound and electrophysiology).
• Design and implement a validation framework for the assessment of the results in terms of detection and classification accuracy.

Academic and Research Environment:

Eindhoven University of Technology (TU/e) is one of Europe’s top technological universities, situated in the heart of one of Europe’s largest high-tech innovation ecosystems. Research at TU/e is characterized by a combination of academic excellence and a strong real-world impact. This impact is pursued via close collaboration with high-tech industries and clinical partners.

Research related to this position will be carried out at the Biomedical Diagnostics (BM/d) lab of the Signal Processing Systems (SPS) group, which is part of the Electrical Engineering department. The BM/d lab, chaired by Prof. Mischi, has a strong track record in electrophysiological signal processing, physiological modelling, and quantitative analysis of biosignals, ranging from ultrasound and MRI to electrophysiology. More specifically for this project, the BM/d lab has also a long tradition in pregnancy monitoring. For more information, see: https://www.tue.nl/en/research/research-groups/signal-processing-systems/biomedical-diagnostics-lab

The candidate will have the opportunity to work with various members of the SPS group and will be tightly collaborating with all the European partners of the KDT NewLife project, in particular with Sencure.

Functie-eisen

We are looking for candidates that match the following profile:

• Master's degree in Electrical/Biomedical Engineering, applied Physics, or related disciplines with excellent grades.
• Excellent knowledge of signal processing and systems.
• Proven programming skills (e.g., in Matlab, Python, C, C++).
• Team player attitude, interested in collaborating with different teams.
• High motivation and creativity.
• Good communication and organization skills.
• Excellent English language skills (writing and presenting).

Additional qualifications:

• Knowledge of electrophysiological signal processing

Arbeidsvoorwaarden

We offer a fixed-term, 2-year position in a research group with an excellent reputation. Salary and benefits are in accordance with the Collective Labour Agreement for Dutch Universities, including:

• Full-time employment for two years.
• 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 TOIO (€2,618).
• A year-end bonus of 8.3% and annual vacation pay of 8%.
• To support you during your EngD and to prepare you for the rest of your career, you will participate in the free personal development program for EngD trainees.
• An excellent technical infrastructure, on-campus children's 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.

Informatie en sollicitatie

Information

Do you recognize yourself in this profile and would you like to know more?
Please contact prof. M. Mischi (m.mischi[at]tue.nl) or dr. E. Peri (e.peri[at]tue.nl).

Visit our website for more information about the application process or the conditions of employment. You can also contact HRServices.Flux[at]tue.nl.

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

Application

If interested, please use 'apply now'-button on this page. You should upload the following:

• a cover letter explaining your motivation and suitability for the position;
• a detailed Curriculum Vitae (including English proficiency level, nationality, VISA requirements, date of birth as well as programming skills, experience overview, publication list (if any), and key achievements in research project(s));
• contact information of two academic references;
• copies of diplomas with course grades;

Candidates will be selected based on graduation mark and proficiency at university including consideration of the reputation of the university, relevant experience and skills, writing skills and publications, work experience as well as performance in interviews.

Application deadline: October 1, 2023

Please keep in mind; you can upload only 5 documents up to 2 MB each.