102 molecular-modeling-or-molecular-dynamic-simulation positions at University of Nottingham
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are coordinated and managed efficiently. We are seeking a candidate that adopts a methodical approach to working in order to achieve work deadlines, has good communication skills and an understanding of molecular
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Based in the Faculty of Engineering at the University of Nottingham, this role will focus on electromagnetic design, modelling and validation of microwave heating technologies for the BioIron
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conduct the research activities into the computational fluid dynamics simulation and optimisation of vortex reactors. You will develop physical and numerical models for the three-dimensional simulation
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filled The overarching aim of this project is to find synergies between methods and ideas of modern machine learning and of statistical mechanics for the study of stochastic dynamics with application
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Supervised by: Rasa Remenyte-Prescott (Faculty of Engineering, Resilience Engineering Research Group) Aim: Develop a mathematical model for obsolescence modelling for railway signalling and telecoms
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, combustion, and process optimisation. The project is focussed on the development of novel interface capturing Computational Fluid Dynamics methods for simulating boiling in Nuclear Thermal Hydraulics
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in healthcare service and opportunities for identification of such deviations using computer vision approaches. It will demonstrate how deviation data can be used in computer-based simulation models
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of mechanical and robotic systems •Ability to use finite element modelling and to simulate complex mechatronics •Ability to implement control and kinematics with hardware-in-the–loop •Background with relevant
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, genes, and pathways involved in sensing water in the model plant Arabidopsis. Building on our previous work (Mehra et al., Science, 2022), we aim to understand how hormone-driven pathways help roots
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utilize preclinical tumour models, high dimensional techniques including spatial mass spectrometry and immunocytochemistry, alongside complementary state-of-the-art molecular biology approaches to identify