PhD Candidate in Molecular Information Processing in Self-organising Dynamic Networks

Are you an aspiring researcher with a chemistry-related degree? Then start your academic career off right as a PhD candidate in the Institute of Molecules and Materials at Radboud University. Join an interdisciplinary project where you can use state-of-the-art instruments to conduct top research on self-organising dynamic networks, while developing your skills and learning new things.
Synthetic materials are typically limited to just one pre-determined function, and rely on electronics for control. One of the largest challenges in the fields of systems chemistry and soft matter is to develop 'intelligent' materials that can directly 'compute' based on molecular input signals and self-organise themselves as a response. Such systems will open fundamentally new modes of material-based function, and enable matter to operate in contexts that cannot be controlled through traditional electronics.

This project establishes an ambitious new step in a chemical system that self-organises to guide molecular inputs along dynamic wires and concomitantly generate functional structures. To this end, we will use self-assembled amphiphilic filaments that grow connections between sender and receiver droplets, and thereby form a network of connections in response to the chemical input that is applied to the system. A recent example of our philosophy - demonstrated by amphiphiles that organise themselves through self-assembly into wire-like networks - can be found in our recent publication . By implementing new feedback and control mechanisms (based on chemical reactions and physicochemical effects), we aim to arrive at a controlled self-organisation of the connections in the network. Ultimately, such a demonstration of molecular information processing in self-organising sender-receiver networks opens potential in neuromorphic systems operative in electronics-free computation.

This research combines experiments and simulations, and varies from molecular self-assembly to reaction networks, Marangoni flow, hydrogels, microfluidics, dedicated microscopy techniques and building dynamic models in programs like Python or Matlab, depending on your personal preferences and the development of the project. You will communicate your findings through publications in peer-reviewed journals and at international conferences, and also be involved in training and teaching BSc and MSc students. Your teaching load may be up to 10% of your appointment.