306 computational-physics-"https:"-"https:"-"https:"-"https:"-"IFM" Postdoctoral positions in United Kingdom
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will have: A PhD in theoretical or computational condensed matter physics, or will expect to obtain one before the start date. Experience in scientific programming. Strong written and verbal
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manufacturing. AI methods will then be applied to this large database to inform optimal processing parameters that will produce components with reliable material properties. The process will be validated in a
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. The process will be validated in a high-demand protective equipment application. You will be responsible for manufacturing and testing of materials, and development of a model to inform material design. You
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physical activity and exercise, nutrition, mental health, and other supportive services. The aim of this project is to evaluate the Cancer Treatment Outcome Programme at the Country Durham and Darlington NHS
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in related program areas to gain exposure to and build knowledge on experimental/research activities and approaches, in order to improve conceptual development and industrial implementation. Identify
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candidate will contribute to an interdisciplinary research programme at the interface of artificial intelligence, biology, and human health. Reporting to the BDI Director, the post holder will play a leading
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Programme Grant on "Quantum Many-Body Physics with Ultracold Polar Molecules'' funded by UK Research and Innovation (UKRI).The research builds upon our expertise in creating ultracold RbCs molecules in
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We invite applications for a Postdoctoral Research Associate in studying the three-dimensional organization of the genome, in the Department of Applied Mathematics and Theoretical Physics
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and Immigration website . Full-Time, Fixed-Term (until 31 August 2028) The Department of Computer Science is seeking a Postdoctoral Research Fellow for the Leverhulme-funded project “Social Mechanisms
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Computer Science, Chemistry, Chemical Engineering, Physics, or Materials Science. You will develop optimisation and machine-learning algorithms for human- and literature-informed discovery of new materials