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Biocomputing with 3D printed neural tissues

Contribute to Materials & Devices for Life Sciences at EIT, redefining nanopore technologies and progressing new approaches in tissue engineering, as a Graduate Ellison Scholar.

Key facts

Project description

Human brains are slower than computers at certain tasks, such as arithmetic. However, brains surpass computers in processing complex information and deal better with fewer and/or uncertain data, such as decision-making on large, incomplete and highly heterogeneous datasets. Further, brains have much lower energy consumption compared to computers. Therefore, brain-like computing (biocomputing) offers potential for building ultra-energy-efficient, highly adaptive learning systems.

Biocomputing has recently been initiated utilising lab-grown 3D human brain tissues (including organoids) to process information. Stem cells, such as induced pluripotent stem cells (iPSCs), are cultured and reprogrammed to grow into organoids: miniatured and functional clusters of neurons. These clusters are placed onto multi-electrode arrays (MEAs) that transmit and receive electrical signals and can help neurons to "learn" tasks.

In this project, we propose to combine 3D neural tissue engineering with biocomputing. Human iPSCs will be differentiated into neurons and glial cells which will be 3D printed and matured during in-vitro culture to generate structurally defined and functional neural tissues. These tissues will be placed on MEAs for electrical stimulation and recording to examine how electrical signal/information leads to structural (e.g. axon formation and synaptic connections) and functional (e.g. calcium activities and neural maturation) changes in the 3D neural tissues. We will also test how electrical training affects neural network connectivity and activity as a ‘learning’ process. Mechanisms involved in these processes will be investigated using molecular biology tools.

The Tissue Engineering Group at Materials and Devices for Life Sciences (MDLS) focus on developing functional 3D human tissues using stem cells for disease modelling, implantation and biocomputing. We have developed droplet 3D-printing and microfluidic techniques for the construction of defined 3D tissues, including neural and cardiac tissues.

We welcome candidates with biology, biophysics, electrophysiology and engineering backgrounds. DPhil researchers will work collaboratively with a multidisciplinary team engaged in cell biology, biophysics, biochemistry, and device and tissue engineering.

Skills Required

  • Degree in medicine, biology, biochemistry, electronic or tissue engineering, or other relevant fields.
  • Electrophysiology and neurobiology
  • Cell and molecular biology
  • Stem cell and organoid culture
  • Experience and interest in multidisciplinary research 

Skills to be Developed

  • Stem cell differentiation
  • 3D printing and microfluidics
  • 3D tissue imaging and characterisation techniques
  • Multi-electrode array measurements and data analysis 

Relevant Background Reading

  1. Nature 647, 306-308 (2025), doi: https://doi.org/10.1038/d41586-025-03633-0
  2. Kagan, B. J. et al. In vitro neurons learn and exhibit sentience when embodied in a simulated game-world. Neuron 110, 3952–3969 (2022). doi: 10.1016/j.neuron.2022.09.001
  3. Zhou, L., Wolfes, A.C., Li, Y., Chen, D.C.W., Ko, H., Szele, F.G. and Bayley, H. Lipid bilayer supported 3D printing of human cerebral cortex cells reveals developmental interactions. Advanced Materials 32, e2002183 (2020). DOI: 10.1002/adma.202002183
  4. Jin, Y., Mikhailova, E., Lei, M., Cowley, S.A., Sun, T., Yang, X., Zhang, Y., Liu, K., Catarino, D., Soares, L.C. and Bandiera, S., 2022. Functional Integration of 3D-Printed Cerebral
  5. Cortical Tissue into a Brain Lesion. Nature Communications 14, 5968 (2023). https://doi.org/10.1038/s41467-023-41356-w
  6. Cruz, E. M., Soares, L. C., et al., Zhou, L., Bayley, H., Molnar, Z., and Szele, F. Astrocyte Enrichment of 3D Cortical Constructs Enhances Brain Repair. Advanced Science, 2026, e07423. https://doi.org/10.1002/advs.202507423 

How to apply

Stage 1: Apply to Ellison Institute of Technology

Submit an application to Ellison Institute of Technology (EIT) by 5pm UK time on Tuesday 1 December 2026.

We encourage you to apply early, as applications will be reviewed as they are received.

Learn more and apply

Stage 2: Apply to the University of Oxford 

If selected by EIT, you will receive conditional funding and will be invited to apply to the University of Oxford by following the instructions on the course page.

Your application will then follow the standard graduate admissions process and will be assessed against the entry requirements shown on the course page.