173 phd-mathematical-modelling-population-modelling Postdoctoral positions at University of Oxford
Sort by
Refine Your Search
-
of 24 months. The project aim’s to develop new constitutive models to describe the mechanical behaviour of Thermoplastic Elastomers (TPEs). These polymers are increasingly being developed as a
-
-funded project entitled “Accelerated Development of Next Generation Li-Rich 3D Cathode Materials (3D-CAT)”. You will have a PhD (or be near completion) in materials or chemistry and experience in battery
-
. To address these questions, we combine a series of interdisciplinary approaches ranging from experimental embryology and fluorescent microscopy to mathematical modelling. The lab is highly interdisciplinary
-
inference attacks, to mitigate privacy leaks in MMFM. You will hold a PhD/DPhil (or be near completion) in a relevant discipline such as computer science, data science, statistics or mathematics; expertise in
-
samples and disease models. Working closely with a dynamic and multidisciplinary team of clinicians and scientists, you will help generate and interpret high-resolution datasets that reveal new insights
-
experimentally investigated. About you You should possess a PhD or DPhil (or be near completion of) in the field of engineering, physics or applied mathematics together with relevant experience in the field
-
with a PhD in Engineering (or close to completion) may apply. You will be responsible for: Design of the first reconfigurable robotic matter in collaboration with world-leading universities and
-
essential that you hold a PhD/DPhil (or close to completion) in mathematics, computational biology, data science, statistics, physics, or a related discipline, and have experience of analysing and
-
and optimising assays aimed at target validation; principally through immunogenicity assays in animal models. You will also conduct experiments aimed at understanding the tumour-immune microenvironment
-
, Oxford, Leeds, Reading, and Birmingham) and international (Utrecht University, ETH Zurich, Université Catholique de Louvain, etc.) scientists to use new modelling resources and methods to elucidate drivers