PostDoc on Fetal movement for fetal wellbeing detection
PostDoc on Fetal movement for fetal wellbeing detection
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The Biomedical Diagnostic (BM/d) Lab at the Eindhoven University of Technology (TUe) is seeking an outstanding PostDoc to work in collaboration with Philips and Máxima Medical Center (MC) in Eindhoven.
Job description
Project description
Pregnancies that are threatened by complications such as asphyxia, are often preceded by slight adaptations in the fetal movement pattern, including reduced fetal movements. Often this is one of the first signs. To improve early detection of fetuses at risk, we will develop reliable and easy-to-use methods to detect fetal movement and its relevant parameters. Early identification allows timely intervention and may thus aid in the prevention of severe complications. The project combines two strengths: physiological insights from physical models with pattern recognition from data-driven models. To this end you will develop algorithms that can be exploited to quantify fetal movements. Availability of accurate detection and prediction fetal movements allows for effective and timely intervention and may thus contribute to improved perinatal outcome. The proposed approach of your research includes: 1) Identification and evaluation of available methods for fetal movement detection, and the physiological relation between specific movement patterns and clinical outcome. 2) Development of a new monitoring modality, capable of reliable and easy-to-use fetal movement in a clinical setting, with potential for transfer to home setting. 3) Performing a feasibility study to verify the new monitoring modality in a (pre)clinical setting. 4) Contributing to setting up a prospective study for testing the new monitoring modality and set-up a database of fetal movement patterns across different risk levels, from which risk stratification will be feasible.
You will contribute to the e/MTIC project 'PISANO' in collaboration with Eindhoven University of Technology, Máxima Medical Center and Philips Research and will work in a multidisciplinary team on all partner locations.
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 has a strong track record in electrophysiological signal processing, physiological modelling and quantitative analysis of biosignals, ranging from ultrasound and MRI to electrophysiology. For more information, see here.
The candidate will have the opportunity to work with various members of the SPS group and will be tightly collaborating with Philips and Máxima MC.
Pregnancies that are threatened by complications such as asphyxia, are often preceded by slight adaptations in the fetal movement pattern, including reduced fetal movements. Often this is one of the first signs. To improve early detection of fetuses at risk, we will develop reliable and easy-to-use methods to detect fetal movement and its relevant parameters. Early identification allows timely intervention and may thus aid in the prevention of severe complications. The project combines two strengths: physiological insights from physical models with pattern recognition from data-driven models. To this end you will develop algorithms that can be exploited to quantify fetal movements. Availability of accurate detection and prediction fetal movements allows for effective and timely intervention and may thus contribute to improved perinatal outcome. The proposed approach of your research includes: 1) Identification and evaluation of available methods for fetal movement detection, and the physiological relation between specific movement patterns and clinical outcome. 2) Development of a new monitoring modality, capable of reliable and easy-to-use fetal movement in a clinical setting, with potential for transfer to home setting. 3) Performing a feasibility study to verify the new monitoring modality in a (pre)clinical setting. 4) Contributing to setting up a prospective study for testing the new monitoring modality and set-up a database of fetal movement patterns across different risk levels, from which risk stratification will be feasible.
You will contribute to the e/MTIC project 'PISANO' in collaboration with Eindhoven University of Technology, Máxima Medical Center and Philips Research and will work in a multidisciplinary team on all partner locations.
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 has a strong track record in electrophysiological signal processing, physiological modelling and quantitative analysis of biosignals, ranging from ultrasound and MRI to electrophysiology. For more information, see here.
The candidate will have the opportunity to work with various members of the SPS group and will be tightly collaborating with Philips and Máxima MC.
Specifications
- max. 38 hours per week
- Eindhoven View on Google Maps
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Eindhoven University of Technology (TU/e)
Requirements
- A PhD degree in Electrical Engineering, Mathematics, Physics or (Bio)medical Engineering.
- Deep knowledge in mathematical modelling, signal processing, stochastical models.
- Some experience with machine-learning algorithms and/or parameter optimization could be a pre.
- An academic attitude and strong analytical mind.
- Enjoy working in a multidisciplinary team with academic, clinical and industrial partners.
- Fluent in spoken and written English.
Conditions of employment
We offer
- a meaningful job in a dynamic and ambitious hospital in close collaboration with Eindhoven University of Technology, with the possibility to present your work at international conferences fixed-term
- a full-time employment for two years in a research group with an excellent reputation, with an intermediate evaluation after one year.
- a gross monthly salary and benefits in accordance with the Collective Labor Agreement for Dutch Universities.
- 30% ruling option: a tax-free allowance equivalent to 30% for the gross salary for foreign applicants moving to the Netherlands
- additionally, 8% holiday and 8.3% end-of-year annual supplements.
- a minimum of 41 holidays per year (excluding bank holidays, for a full-time employment of 40 hrs/week)
- additional benefits, including excellent technical infrastructure, childcare, holiday savings schemes, and sports facilities.
- assistance for finding accommodation is offered.
- a personal development program aimed to develop your social and communication skills (see http://www.tue.nl/PROOF3TU).
