PhD - Automated Assessment of Cerebral Autoregulation and Coupled Dynamics Using NIRS & EEG Scoring (KU Leuven ESAT - STADIUS, Stadius Centre for Dynamical Systems, Signal Processing and Data Analytics)

AUTOMATED ASSESSMENT OF CEREBRAL AUTOREGULATION AND COUPLED DYNAMICS USING NIRS & EEG SCORING This project is hosted by the BioMedical data Processing research group BioMed within the division Stadius of the Department of Electrical Engineering (ESAT) at KU Leuven. BioMed focuses on the development of numerical algorithms and software for biomedical signal processing in close collaboration with the University Hospitals. The Stadius Center for Dynamical Systems, Signal Processing, and Data Analytics (STADIUS) is an academic research center, with a research focus on mathematical engineering, where mathematical tools from numerical linear and multilinear algebra, statistics and optimization are engineered for applications of dynamical systems and control, signal processing, data modeling and analytics. Project This position is one of the 15 ESR positions of the Marie Skłodowska-Curie Innovative Training Network “INFANS - INtegrating Functional Assessment measures for Neonatal Safeguard", funded by the European Union’s Horizon2020 Research and Innovation Programme. The goal of INFANS is to develop a new neonatal brain monitoring system, designed to overcome the severe shortage of clinically viable means to high quality monitor the brain function in infancy, crucial to prevent later life neurological, cognitive and motor impairment. To accomplish this goal, INFANS established a structured European PhD training programme in biomedical engineering, signal processing and clinical procedures to train a new generation of creative and entrepreneurial young researchers. The individual research projects of the ESR encompass the topics technological innovation, industrial development, clinical validation, identification of neonatal healthcare needs. As part of their research the INFANS ESRs will develop a novel platform for high quality, clinically-viable monitoring combining Electro-Encephalography (EEG) with Near-InfraRed Spectroscopy (NIRS) and accessible worldwide. Well-targeted visits and secondments, soft skills and dynamic training activities, an Open Science strategy, extensive involvement of ESRs in the network events organization, extensive contacts with other research, training and industrial European networks, dissemination activities and the award of doctoral degrees are further assets offered to INFANS ESRs. The goal of the ESR10 project is to develop software for automated EEG scoring, cerebral auto regulation (CAR) assessment and quantification of linked dynamics between EEG activity and cerebral oxygenation (NIRS), for use in computer-aided prediction of neurological outcome in neonates in neonatal intensive care units (NICUs). More specifically, the ESR 10 will develop advanced algorithms (graphs using appropriate kernels, multiscale entropy, tensor-based Blind Source Separation, fractals, subspace projections) for the joint analysis of EEG and NIRS measurements. Time-frequency features will be derived as a marker for brain recovery (after any damage), and will also be used for the automatic detection of sleep stages in newborns. NIRS measurements (surrogates for cerebral blood flow) are used to assess cerebral autoregulation (CAR) via advanced nonlinear methodologies. The combination of all extracted features is used as input to clinically interpretable machine learning classifiers (Support Vector Machines, convolutional neural networks) to determine the severity of EEG abnormalities, and evaluate the combined use of EEG and NIRS scores as biomarkers for (non)pathological condition. These scores are used also to develop functional growth charts for normal neural development in neonates/infants. The ESR 10 will develop the software toolbox to quantify the linked dynamics between EEG and NIRS measurements which should run in real-time at bedside in NICUs and be tested on clinical data provided by hospitals in Helsinki and Utrecht. Profile You should have a master's degree in information technology, biomedical engineering, electrical or mathematical engineering, artificial intelligence, or a similar degree with an equivalent academic level. A genuine interest in biomedical imaging and research should motivate your application. The candidate should have strong social abilities allowing an active participation to the European network, fruitful exchanges with other students and researchers, and an excellent integration in the team of your research group. You should be ready and able to travel in Europe for the network meetings as well as for sharing the experience with your secondment team. Offer Duration: 36 Months (extendable with maximally 12 months to finish the PhD) The selected candidate will be able to take advantage of the unique set-up of the INFANS network, encompassing 6 academic and 4 industrial partners from 6 EU countries, among which leading universities, companies and clinical institutions. Excellent science, industrial leadership and societal challenge are merged in the INFANS network.The partners involved in INFANS share complementary expertise and facilities to provide international, interdisciplinary and intersectoral research training and mobility that will complement local doctoral training. The INFANS ESRs will become independent researchers with improved career prospects in both the academic and non-academic sectors, and will advance the EU capacity for innovation in biomedical engineering. Eligibility and Mobility Rule: Early-Stage Researchers shall, at the time of recruitment by the host organisation, be in the first four years (full-time equivalent research experience) of their research careers and have not been awarded a doctoral degree. At the time of recruitment by the host organisation, researchers must not have resided or carried out their main activity (work, studies, etc.) in the country of their host organisation for more than 12 months in the 3 years immediately prior to the reference date. Interested? For more information please contact Prof. dr. ir. Sabine Van Huffel, tel.: +32 16 32 17 03, mail: sabine.vanhuffel@kuleuven.be. You can apply for this job no later than February 01, 2019 via the online application tool KU Leuven seeks to foster an environment where all talents can flourish, regardless of gender, age, cultural background, nationality or impairments. If you have any questions relating to accessibility or support, please contact us at diversiteit.HR@kuleuven.be. If you apply for this position please say you saw it on Engineeroxy

AUTOMATED ASSESSMENT OF CEREBRAL AUTOREGULATION AND COUPLED DYNAMICS USING NIRS & EEG SCORING

This project is hosted by the BioMedical data Processing research group BioMed within the division Stadius of the Department of Electrical Engineering (ESAT) at KU Leuven. BioMed focuses on the development of numerical algorithms and software for biomedical signal processing in close collaboration with the University Hospitals. The Stadius Center for Dynamical Systems, Signal Processing, and Data Analytics (STADIUS) is an academic research center, with a research focus on mathematical engineering, where mathematical tools from numerical linear and multilinear algebra, statistics and optimization are engineered for applications of dynamical systems and control, signal processing, data modeling and analytics.

Project

This position is one of the 15 ESR positions of the Marie Skłodowska-Curie Innovative Training Network “INFANS - INtegrating Functional Assessment measures for Neonatal Safeguard", funded by the European Union’s Horizon2020 Research and Innovation Programme.

The goal of INFANS is to develop a new neonatal brain monitoring system, designed to overcome the severe shortage of clinically viable means to high quality monitor the brain function in infancy, crucial to prevent later life neurological, cognitive and motor impairment. To accomplish this goal, INFANS established a structured European PhD training programme in biomedical engineering, signal processing and clinical procedures to train a new generation of creative and entrepreneurial young researchers.

The individual research projects of the ESR encompass the topics technological innovation, industrial development, clinical validation, identification of neonatal healthcare needs. As part of their research the INFANS ESRs will develop a novel platform for high quality, clinically-viable monitoring combining Electro-Encephalography (EEG) with Near-InfraRed Spectroscopy (NIRS) and accessible worldwide. Well-targeted visits and secondments, soft skills and dynamic training activities, an Open Science strategy, extensive involvement of ESRs in the network events organization, extensive contacts with other research, training and industrial European networks, dissemination activities and the award of doctoral degrees are further assets offered to INFANS ESRs.

The goal of the ESR10 project is to develop software for automated EEG scoring, cerebral auto regulation (CAR) assessment and quantification of linked dynamics between EEG activity and cerebral oxygenation (NIRS), for use in computer-aided prediction of neurological outcome in neonates in neonatal intensive care units (NICUs). More specifically, the ESR 10 will develop advanced algorithms (graphs using appropriate kernels, multiscale entropy, tensor-based Blind Source Separation, fractals, subspace projections) for the joint analysis of EEG and NIRS measurements. Time-frequency features will be derived as a marker for brain recovery (after any damage), and will also be used for the automatic detection of sleep stages in newborns. NIRS measurements (surrogates for cerebral blood flow) are used to assess cerebral autoregulation (CAR) via advanced nonlinear methodologies. The combination of all extracted features is used as input to clinically interpretable machine learning classifiers (Support Vector Machines, convolutional neural networks) to determine the severity of EEG abnormalities, and evaluate the combined use of EEG and NIRS scores as biomarkers for (non)pathological condition. These scores are used also to develop functional growth charts for normal neural development in neonates/infants. The ESR 10 will develop the software toolbox to quantify the linked dynamics between EEG and NIRS measurements which should run in real-time at bedside in NICUs and be tested on clinical data provided by hospitals in Helsinki and Utrecht.

Profile

You should have a master's degree in information technology, biomedical engineering, electrical or mathematical engineering, artificial intelligence, or a similar degree with an equivalent academic level. A genuine interest in biomedical imaging and research should motivate your application. The candidate should have strong social abilities allowing an active participation to the European network, fruitful exchanges with other students and researchers, and an excellent integration in the team of your research group. You should be ready and able to travel in Europe for the network meetings as well as for sharing the experience with your secondment team.

Offer

Duration: 36 Months (extendable with maximally 12 months to finish the PhD)

The selected candidate will be able to take advantage of the unique set-up of the INFANS network, encompassing 6 academic and 4 industrial partners from 6 EU countries, among which leading universities, companies and clinical institutions. Excellent science, industrial leadership and societal challenge are merged in the INFANS network.The partners involved in INFANS share complementary expertise and facilities to provide international, interdisciplinary and intersectoral research training and mobility that will complement local doctoral training. The INFANS ESRs will become independent researchers with improved career prospects in both the academic and non-academic sectors, and will advance the EU capacity for innovation in biomedical engineering.

Eligibility and Mobility Rule: Early-Stage Researchers shall, at the time of recruitment by the host organisation, be in the first four years (full-time equivalent research experience) of their research careers and have not been awarded a doctoral degree. At the time of recruitment by the host organisation, researchers must not have resided or carried out their main activity (work, studies, etc.) in the country of their host organisation for more than 12 months in the 3 years immediately prior to the reference date.

Interested?

For more information please contact Prof. dr. ir. Sabine Van Huffel, tel.: +32 16 32 17 03, mail: sabine.vanhuffel@kuleuven.be.

You can apply for this job no later than February 01, 2019 via the online application tool

KU Leuven seeks to foster an environment where all talents can flourish, regardless of gender, age, cultural background, nationality or impairments. If you have any questions relating to accessibility or support, please contact us at diversiteit.HR@kuleuven.be.

If you apply for this position please say you saw it on Engineeroxy

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