Open positions in the Endres group
3-year PhD in Physics of Life
Physics of life is an exciting scientific discipline at the border of physics and biology, aimed to explain biological complexity and emergent function based on physical principles. Influences in this area come from statistical mechanics, physics of phase transitions, far-from-equilibrium physics, active matter, collective behaviour, dynamical systems theory, and machine learning – just to name a few. For this PhD position, funded by the Department of Life Sciences at Imperial College, the applicant can choose a project from a variety of topics, depending on the applicant’s interest:
​
How to build robust spatial patterns?
Self-organising patterns and structures are abundant in biological systems (e.g. fur patterns, bone and brain structures etc), but understanding or even engineering these remains elusive. Experimental systems are complex, robust, yet flexible, while mathematical models of pattern formation, foremost the seminal Turing instability, are simple and require fine-tuning. How does nature compute robust patterns, e.g., when laying out the body plan during embryogenesis? This project is based on data from synthetic biologist Prof. Mark Isalan, and links mechanistic modelling and artificial intelligence for solving the inverse problem.
​
Unifying cellular programs: merging chemotaxis and phagocytosis
This proposal aims to study how cells make decisions in response to combined chemotactic and phagocytic stimuli. Despite their tight coordination during an immune response, these behaviors are typically studied in isolation. It remains unclear how shared cellular resources, such as the membrane, cytoskeleton, and signaling components, are allocated. Our hypothesis is that cells make either-or decisions for conflicting stimuli due to limited resources and physical constraints, but we also believe that synergistic effects can occur if stimuli are aligned. By applying our new spatio-temporal theoretical framework, we aim to unify cellular programs. There are a number of international experimental collaborators on this project.
​
Physical limits of accurate sensing
Biological cells can sense near the physical limits, set by effectively counting individual molecules. This is a noisy process as in chemical concentration and gradient sensing molecules arrive randomly at the cell surface by diffusion. While Berg and Purcell (1977) suggested that cells average noisy signals to improve the accuracy, cells can evolve other strategies such as maximum likelihood estimation. All these processes require energy consumption. In this project, we will explore at a fundamental level how receptors can use nonequilibrium processes and clustering for accrurate sensing.
​
Mechanical intelligence: how cell body is linked to computation
Mechanical intelligence is widespread in nature, by which information processing is deeply embedded in the architecture of living systems. For instance, the underlying mechanisms by which cells perform chemotaxis, the directed movement of an organism along a chemical concentration gradient remains a subject of intensive research. Particularly relevant is the understanding of the tight coupling between sensory cues and cell locomotion mechanisms, as they provide insights into effective navigation methods at the microscopic scale for cell sensing at fundamental physical limits. Here, we focus on studying the role of pseudopod formation as a cellular decision-making mechanism, which represents an important yet not fully understood aspect of cellular navigation.
​
How cells become cognitive agents to anticipate the future
Biological systems show emergent collective behaviour based on simple rules governing the decisions of each individual agent. These can be simulated in silico to gain a better understanding of how basic principles and information private to each agent can lead to such emergent collective behaviour. Here, we will investigate different models for how agents can harvest information from their surrounding space to plan their next moves, by maximising future possibilities. We will use these causal-entropy models for physical intelligence to simulate systems of many interacting agents and exploring how cells might follow these principles to organise themselves during embryonic development.
The interested student should have a solid physics, math, or bioengineering background with strong computational expertise, and interest in working on biological data and collaborating with biologists.
Funding and Eligibility
The studentship will cover UK tuition fees and will provide an annual tax-free maintenance stipend at the standard UKRI level, currently at £21,237 (rising annually by an amount linked to inflation), in 12 monthly instalments. Studentships will be funded for a maximum of 36 months, subject to satisfactory progress. A BSc in biological, or related, sciences is required at Upper Second Class level or better and candidates with a master's degree, in addition to the BSc, might be given preference. Candidates must be UK nationals (EU candidates with settled status in the UK may be considered). International students are not eligible.
​
How to apply
Applicants - please send your CV, personal statement (explaining your motivation to apply and interests), as well as the contact details of two referees to me. Shortlisted students will be interviewed by a panel of supervisor and members of the department.
For more information: https://www.findaphd.com/phds/program/department-of-life-sciences-funded-phd-studentships/?p5911
Deadline for applications 6 January 2025, 12 noon.
​​
​
3-year PhD in modelling 3D cell migration in cancer
With co-supervisors Prof. Chris Bakal (Institute of Cancer Research) and Dr. Deniz Akyildiz (Department of Mathematics at Imperial College), funded by the EPSRC Centre for Doctoral Training in Statistics and Machine Learning (CDT).
​
In this multidisciplinary project, the PhD student will develop mechanistic modelling and and generative AI to predict morphodynamics of melanoma cells in 3D environments, using both fixed image data and time-series datasets. For this purpose, the student will initially explore the morphodynamic space to model how cell shape changes underpin invasion, and migration – identifying shapes and morphodynamics that may be relevant to metastasis in vivo. These models will serve to constrain subsequent generative approaches to predict the shape of metastatic/invasive cells as single cells, then in tumours, and ultimately then identify these shapes in patient biopsies.
Apply for studentship
While you are strongly advised to contact the supervisors to discuss the project and suitability, applications are done via:
Top selected students by the CDT panel can then choose a project. Deadline is Wednesday 8th January 2025
​
​
​Imperial PhD scholarships for high-performance students
​There are two types of prestigious scholarships provided by Imperial College. The President's scholarships require a BSc and Masters degrees at 1st class and Distinction levels respectively and are open to all irrespective of nationality. The Schroedinger scholarship only funds UK or EU students but without the 3-year residency requirement (overseas/non-European students are not eligible). Please see following links for application details: