Life at the microscale is noisy, inevitably impacted by thermal fluctuations. On the one hand, noise plays a negative role, hampering the ability to perform tasks reliably. On the other hand, systems that are suitably driven out of equilibrium can exploit fluctuations to achieve transport, efficient energy conversion, and build biochemical circuits and switches. How do living systems deal with fluctuations without being overwhelmed by them? How do cells employ their stochastic machinery to process noisy signals and nonetheless perform tasks robustly? How much does this cost them? Is it possible to exploit fluctuations to design efficient microscopic engines? The PhD project will address these general questions from the theory viewpoint by focusing on specific biological systems such as biomolecular condensates, molecular motors, etc…, within ongoing experimental collaborations. We aim to understand how fluctuations originating at the molecular scale propagate to larger scales, how they are affected by larger-scale processes, and, ultimately, how they give rise to macroscopic consequences. The prospective student will investigate these topics within the framework of non-equilibrium thermodynamics of small systems, making use of, and developing tools from stochastic processes, stochastic optimal control, information theory, and machine learning. Concerning machine learning, special attention will be devoted to the interpretability of the methods.
Applicants should have, or expect to have, an integrated Master’s (e.g., MSci) with first-class honours or upper division second-class honours (2:1), or a BSc plus Master’s (MSc) degree with Merit or Distinction in Physics, Biophysics, Applied Mathematics, or related subject. The successful applicant will demonstrate strong interest and motivation in the subject, and ability to think critically and creatively. Previous research experience in theoretical physics and or an interdisciplinary research environment is desirable.
Interested candidates should initially contact the supervisor (Stefano Bo, [Email Address Removed]) with a transcript, CV, and motivation letter expressing interest in the project. Informal enquiries are encouraged.
The selection process will involve a pre-selection on documents, if selected this will be followed by an invitation to an interview. All shortlisted applicants will be invited to interview no more than 4 weeks after the application deadline.