Research Assistant / Associate: Modelling Marine Calcification Mechanisms (Fixed Term)

The successful candidate will work closely with the PI and a PhD student within a larger cross-disciplinary team to construct a quantitative computational model of carbonate biomineralisation processes.

Carbonate biomineralisation is a key process in global carbon cycling, but there are major gaps in our understanding of how biominerals form. We lack a quantitative understanding that can predict the formation rates or composition of a biominerals from known environmental conditions. This project aims to construct such a model.

The ultimate goal is to create a general framework for predicting the composition and formation rates of marine carbonate biominerals as a function of taxonomy and environmental conditions. The model will be informed by physiological and geochemical measurements of samples grown under controlled conditions designed to reveal the underlying mechanisms of biomineralisation in marine calcifying organisms.

The task of this PDRA is to assist in the design of a numerical model of biomineralisation processes, informed by the physical and chemical processes that underpin biomineralisation in context of extensive literature in this field. The PDRA will then parameterise and test that model by integrating biological (transcriptome, proteome, physiology) and geochemical (trace element and isotopic ratios) data collected by the rest of the project team. Finally, we will explore the application of this model to predict future marine calcification rates, and invert the model to enable the robust interpretation of past climate records from biomineral composition.

The successful candidate will have (or be about to obtain) a PhD in the broad area of Computational Modelling applied to geochemical or biological systems, and be comfortable working routinely in modern programming languages (e.g. Python, Julia, Rust) and using standard software development and collaboration platforms (e.g. GitHub).

Training for specific tasks can be provided, and the candidate will be mentored and supported in developing their career and research interests. Owing to the collaborative nature of the project, the candidate will be expected to be present in Cambridge for the majority of the post.