Winter-Hjelm, Nicolai

ETH Postdoctoral Fellow  

Dr. Nicolai Winter-Hjelm
  • GLC F 18
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Inst. f. Biomedizinische Technik
Gloriastrasse 37/ 39
8092 Zürich
Switzerland

Dr.  Nicolai Winter-Hjelm

Looking for a student project?

I am always looking for motivated students from diverse backgrounds—such as biomedical engineering, biophysics, neuroscience, nano- and microtechnology, and biotechnology— for student projects, including master’s theses, semester projects, or bachelor’s theses.

My research focuses on bottom-up neuroscience, aiming to build in vitro neural models to study Alzheimer’s disease. I use a combination of microfluidic systems to design anatomically relevant neural microcircuits in the lab, electrophysiology to analyze their behavior, as well as iPSC technology to develop more accurate models for bridging preclinical and clinical neuroscience.

If you're interested, please send me an email with your CV, transcript of records, and a brief statement of motivation. Please also include any other relevant experience. Together, we can find a project that suits your skills and interests.  

Background

I earned my Master’s degree in Nanotechnology, specializing in Bionanotechnology, from the Norwegian University of Science and Technology (NTNU) in 2020. In 2019, I participated in an exchange program at the School of Biological Sciences, Nanyang Technological University. My Master's thesis focused on using microfluidic interfaces with microelectrode arrays to study action potential propagation between individual neurons.

From 2020 to 2024, I completed my PhD at NTNU in the Group for Integrated Neuroscience, under the supervision of Professors Ioanna Sandvig and Pawel Sikorski. During my PhD, I developed engineered neural networks to study neural function and dysfunction, with a particular focus on diseases like Alzheimer's and ALS. I introduced multi-nodal microfluidic platforms with directed connectivity to create anatomically relevant, computationally complex networks. By introducing patient-derived cells and pathological factors like amyloid beta and tau, we demonstrated the potential of these platforms to model disease mechanisms in a more physiologically relevant context. I also introduced 3D structured interfaces using inclined lithography to support the growth of multi-layered neural networks integrated with microelectrode arrays (MEAs), enabling more complex network dynamics than traditional 2D systems. Additionally, I developed a reproducible fabrication protocol for nanoporous microelectrodes, enhancing the quality of electrophysiological recordings and providing a better understanding of neural network behavior.

Research Interests

In my postdoctoral work, I plan to advance the above-mentioned technologies by applying high-density MEAs and genetically engineered iPSCs to create even more sophisticated models of Alzheimer’s disease. My research focuses on improving the underlying platforms and tools—such as better microfluidic interfaces, more precise microelectrode arrays, and enhanced cell-culturing techniques—to create neural models that more accurately reflect the complexities of disease progression. By refining these technologies, I aim to bridge the gap between preclinical and clinical neuroscience, reducing the reliance on animal models while enabling earlier, more precise detection of neurological disorders.

In the long term, I aspire to contribute to the development of advanced, technology-driven solutions for personalized medicine in Alzheimer's and other neurological disorders. By improving the capabilities of engineered neural platforms, I hope to facilitate early detection, better disease modeling, and more effective therapeutic interventions. My goal is to create systems that not only improve our understanding of the neural microcircuits involved in disease progression but also enable more targeted, personalized treatments. This approach will ideally shift the focus from symptom management to early intervention, improving patient outcomes and reducing the overall burden of neurological diseases.

My motivation stems from a deep personal interest in the intersection of biology and technology, and the transformative potential it holds to advance both our understanding and treatment of neurological disorders.

I am always eager to connect with students, researchers, and innovators in neuroengineering, biomedical engineering, and related fields. Feel free to reach out for collaborations or to discuss the future of neuroscience research.

Publications

external page Nanoporous platinum microelectrode arrays for neuroscience applications. N. Winter-Hjelm, L. Isdal, P. Köllensperger, A. Sandvig, I. Sandvig & P. Sikorski. RSC Advances (2025).

external page Functional complexity of engineered neural networks self-organized on structured 3D interfaces. N. Winter-Hjelm, K. G. Klausen, A. S. Normann,  A. Sandvig,  I. Sandvig & P. Sikorski. Small (2025).

external page ALS patient-derived motor neuron networks exhibit microscale dysfunction and mesoscale compensation rendering them highly vulnerable to perturbation. V. Fiskum, N. Winter-Hjelm, N. Christiansen, A. Sandvig & I. Sandvig. bioRxiv (2025).

external page Evolving alterations of structural organization and functional connectivity in feedforward neural networks after induced P301L tau mutation. J. S. Weir, K. S. Hanssen, N. Winter-Hjelm, A. Sandvig & I. Sandvig. European Journal of Neuroscience (2024).

external page Engineered cortical microcircuits for investigations of neuroplasticity. N. Winter-Hjelm, P. Sikorski, A. Sandvig & I. Sandvig. Lab on a Chip (2024). 

external page Reverse engineering of feedforward cortical-Hippocampal microcircuits for modelling neural network function and dysfunction. K. S. Hanssen*, N. Winter-Hjelm*, S. N. Niethammer, A. Kobro-Flatmoen, M. P. Witter, A. Sandvig & I. Sandvig. *Shared first-authorship. Nature Scientific Reports (2024).  

external page Structure-function dynamics of engineered, modular neuronal networks with controllable afferent-efferent connectivity. N. Winter-Hjelm, Å B. Tomren, P. Sikorski, A. Sandvig & I. Sandvig. Journal of Neural Engineering (2023).  

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