The research will involve theoretical work in information theory as well as computer simulations. It will investigate complex systems approaches to one of the most fundamental problems in systems biology: emergence of universal coding, considered as an innovation-sharing protocol in evolutionary dynamics. The PhD will be supervised by Prof. Mikhail Prokopenko. The applicant will join the Complex Systems Research Group (CSRG) at The School of Civil Engineering – The University of Sydney. The CSRG group comprises ten academics, and has wide collaborations across the University, Australia, and internationally. It is a vibrant, world-leading group in the fields of guided self-organisation and critical phenomena forecasting.
One of the most fundamental problems in systems biology is the definition and understanding of “the gene”. For example, Carl Woese presents the real problem of the gene as “how the genotype-phenotype relationship had come to be”. Arguably, the reason for this increase in complexity can be identified with specific communication mechanisms within a complex sophisticated network of interactions, which are exhibited by translationally produced proteins, multi-cellular organisms, and social structures in general. The evolution of the translation mechanism is a complex process, and we may only intend to analyse its simplified models. However, in doing so this PhD study shall take a principled approach and consider a computational model of evolutionary dynamics in a generic information-theoretic way, aiming to suggest mechanisms resolving Eigen’s paradox. Specifically, the project will develop new computational information‐theoretic model for evolutionary dynamics approaching the “coding threshold”. In addition, the study will analyse how different proto‐cells could stigmergically share such information within a self-organising innovation-sharing protocol, leading to universal encoding.
Applicants need to satisfy the eligibility criteria for PhD enrolment at The University of Sydney. Backgrounds in applied mathematics, physics, computer science, and specifically in information theory, complex networks and statistical mechanics will be beneficial. The successful applicant will demonstrate a strong commitment to academic research in the proposed field. He/she will have excellent written and oral communication skills, as well as demonstrated ability to program in MATLAB, Java, or C++, and will be willing to create and develop original approaches to tackle open questions. Applications should be sent by email to Prof. Mikhail Prokopenko: email@example.com They should include a Resume and a Cover Letter. In their Cover Letter, applicants are invited to include a short (about 250 words) research statement explaining how they understand the issues related to the topic of research.
The opportunity ID for this research opportunity is 1947