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PhD Studentship: Advancing solid-state battery electrolyte manufacturing with terahertz spectroscopy
Bachelors, or Masters degree in Electronic, Chemical Engineering, Applied Physics, Physical Sciences or equivalent. Experience in more than one of the following topics will be a plus: Working knowledge of
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computational and mathematical techniques to problems with global significance. Interdisciplinary Training – Students gain expertise across physics, engineering, computer science, and applied mathematics
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, but not necessary to apply for the position. How to apply: Please choose Electrical and Electronic Engineering Research Program and Control and Power Group, then indicate Professor Balarko Chaudhuri as
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unique experimental platform developed in the Bakshi Lab (https://www.bakshilab.net/ ) that enables time-resolved measurements of individual bacterial cells throughout the phage infection process. The post
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of biomimetics by developing artificial nanochannels inspired by biological mechanosensitive receptors. With a focus on mimicking the exquisite touch, force, pressure, and nuanced responses to various physical
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then be fed into process-level flowsheet models. The UK-National Nuclear Laboratory (UK-NNL) is supporting this project. In addition to acquiring training in computational modelling and theory
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techniques to problems with global significance. Interdisciplinary Training – Students gain expertise across physics, engineering, computer science, and applied mathematics, developing versatile skills
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outside the UK, in a relevant area of Physical Science, Materials Science, or Engineering. You should be able to demonstrate some computational capabilities (e.g. evidencing a 2:1 or higher in relevant
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advantages in terms of materials modelling and contact, COMSOL offers the potential to capture a fuller range of physical behaviours. Chiefly, the ability to capture the inertial behaviour of fuel pellet
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major £10 million national research programme bringing together leading experts in cancer epidemiology, biostatistics, artificial intelligence, and health data science. THE PROJECT: Early cancer diagnosis