The Clinical Neurophysiology group is seeking an Assistant Professor with a background in (applied) physics, electrical engineering, or biomedical engineering, and proven expertise in experimental neurophysiology.
You will contribute to our research on neuronal dynamics during metabolic stress, with a particular focus on in-vitro research related to hypoxic/ischemic injury and stroke. This research aims to elucidate the underlying neuronal dynamics during metabolic stress, and various forms of stimulation to improve recovery, with the ultimate goal of translating these findings to clinical practice.
In addition to research, you will play an active role in education, including teaching neurophysiology and biophysics to students of the Technical Medicine and Biomedical Engineering programs, as well as supervising Bachelor’s and Master’s students.
Our research is highly translational, addressing clinical challenges in metabolic stress and epilepsy with a strong focus on enhancing our understanding of pathophysiology, improving diagnostics and prognostication, and developing innovative treatments. We utilize biophysical modeling alongside clinical data, with experimental work involving cultured neurons on multi-electrode arrays (MEAs). The group also maintains strong national and international collaborations with clinical and preclinical research groups.
Information and application
Are you interested in this position? Please send your application via the 'Apply now' button below before 8 December 2024, and include:
Examples; a CV, research and education statement, and list of publications
About the department
Mission statement and research lines Clinical Neurophysiology group (CNPH)
Research in the Clinical Neurophysiology group is at the interface of neuroscience, neurophysiology, and clinical neurology, focusing on cerebral ischemia and epilepsy. In addition, to improve understanding of pathophysiology, we aim to develop novel diagnostic tools and treatments. Our research is truly translational: from the UT to the clinic and back.
The EEG is a key clinical and research tool. EEG signal analysis includes various machine learning techniques to improve diagnostic values and (bedside) application. Applied EEG studies are complemented by biophysical modeling and simulation for improved understanding of underlying neuronal dynamics and prediction of treatment effects. In addition, we use in vitro models consisting of cultured neurons (from rodent or human induced pluripotent stem cells) on multi-electrode arrays to study basic neuronal and synaptic functioning, identify treatment targets, and screen treatments.
About the organisation
The Faculty of Science & Technology (Technische Natuurwetenschappen, TNW) engages some 700 staff members and 2000 students in education and research on the cutting edge of chemical technology, applied physics and biomedical technology. Our fields of application include sustainable energy, process technology and materials science, nanotechnology and technical medicine. As part of a people-first tech university that aims to shape society, individuals and connections, our faculty works together intensively with industrial partners and researchers in the Netherlands and abroad, and conducts extensive research for external commissioning parties and funders. Our research has a high profile both in the Netherlands and internationally and is strengthened by the many young researchers working on innovative projects with as doctoral candidates and post-docs. It has been accommodated in three multidisciplinary UT research institutes: Mesa+ Institute, TechMed Centre and Digital Society Institute.
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