About Vinuniversity
VinUniversity (VinUni: [protected info]) is the first private, not-for-profit Vietnamese university established based on international standards. The university integrates the models of excellent international universities with the unique cultural and economic characteristics of Vietnam, to make a breakthrough in Vietnamese higher education and to become a world-class university.
The University has built strategic collaborations with Cornell University and the University of Pennsylvania and Nanyang Technological University- a choice that speaks to our commitment to excellence, innovation in research and teaching, and to making a difference in the world.
VinUni comprises of College of Arts and Sciences; College of Business and Management; College of Engineering and Computer Science; and College of Health Sciences.
Every aspect of the University: its curricula, research, faculty, student body, facilities, and campus life, is being developed to meet the highest standards set by the world's leading accrediting and ranking organizations, such as FIBAA, ABET, AACSB, AGCME-I, Quacquarelli Symonds (QS) and Times Higher Education (THE).
VinUni's founding benefactor - Vingroup is one of the biggest private conglomerates in Asia with the largest market capitalization value in Vietnam. As a multisector corporation, Vingroup focuses on main areas: Industrials &
Technology
Real Estate &
Services
Social Enterprises. VinUni is proud to be a part of the Vingroup ecosystem, giving its students opportunities to connect with several high quality research institutes, pioneering companies (such as VinFast, Vinpearl, Vinmec, Vinschool, and Vinhomes) and an dynamic entrepreneurial ecosystem (such as VinVenture, VinMotion, and VinRobotics...).
In September 2024, VinUni became the youngest and fastest university in the world to achieve QS 5 stars, earning 5 stars in 9 categories: global engagement, good governance, program strength, academic development, teaching, employability, facilities, arts, and social impact. In October 2024, VinUni was appointed by UNESCO as the first and only UNESCO University Chair, focusing on Environmental Leadership, Cultural Heritage, and Biodiversity.
Project Description
Epilepsy affects 1% of the world's population. Up to 30% suffer from drug‐resistant epilepsy (DRE), out of which more than 30% do respond favorably to surgery though only a small fraction can undergo neuromodulation (single-pulse electrical stimulation-SPES). Effective tools are needed to identify candidates for right intervention before applying brain resection planning.
Lack of an intelligent technique deprives clinicians from discovering robust biomarkers, relating scalp signatures to intracranial networks, and moving neuromodulation beyond bespoke experimentation into protocol‐driven care.
This Postdoctoral Research Assistant (PDRA) will build upon 20 years of joint research with epileptologists in the UK reflected in over 50 publications, the unique data recorded in King's College London (KCL) Hospital, developed methods for identification of both interictal epileptiform discharges (IEDs) as well as delayed responses to SPES, and the previous surgery outcomes, to develop a unified expert system for automatic localization of seizure network, translate scalp to intracranial EEG data, and most importantly rank the surgical target and predict the recovery brain resection outcome. Patient demands and rapid establishment of new neuromodulation centers across the world confirm the urgency for doing this project.
The objectives are 1) delineation of seizure propagation networks, 2) relating scalp-EEG features to intracranial markers, 3) ranking candidate resection/ablation targets and 4) estimating the probability of patient response to neuromodulation and the corresponding parameter ranges.
KEY SELECTION CRITERIA
Required The applicant will be based in College of Engineering and Computer Science in Hanoi, Vietnam, supervised by a team including both engineers and clinicians, leading by Professor Saeid Sanei, and will collaborate with the Institute of Psychiatry, Psychology, and Neuroscience (IoPPN) in KCL. The candidate is required to:
Have a PhD in Signal Processing, Machine Learning, or Bioengineering from a reputed university. Have a strong background in the related subjects in advanced/adaptive signal processing (e.g. array processing, multiway signal processing, and sparsity), machine learning, and familiarity with seizure electroencephalography (EEG) analysis. Be fluent in reading, writing, and communicating in English.
CONTACT
Interested applicants for the advertised postdoctoral position should contact Prof. Saeid Sanei by email at [protected info].
We thank all applicants for their interest. Please note that only those candidates selected for interviews will be contacted.
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