664 data-"https:" "https:" "https:" "https:" "https:" "https:" "https:" "Univ" "Univ" "UNIV" positions at University of Sheffield
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silk extrusion, which will guide attempts to produce synthetic silk in the lab. Please apply for this project using this link: https://www.sheffield.ac.uk/postgraduate/phd/apply/applying Funding Notes
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experience. Desirable Interview/ Application Further Information Grade 2 Salary £23,061 to £23,350 pro rata, per annum. With the potential to progress to £23,742 pro rata, per annum, through sustained
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/systems theory and optimization is desirable. Full details of how to apply can be found at the following link: https://www.sheffield.ac.uk/acse/research-degrees/applyphd Applicants can apply for a
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Application Deadline: 04 February 2026 Details 1. Background and Research Rationale: In our complex and ever-changing world, humans are constantly faced with a flood of sensory information. To make effective
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, passive scalar in flows and flows through porous media using OpenFoam. Highly Desirable Application/Interview Excellent data analysis skills, with experience post-processing large volumes of computational
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participants within antenatal and maternity settings and provide clear, sensitive information about the study to potential participants. They will obtain informed consent in accordance with Good Clinical
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Research Application form available here: https://www.sheffield.ac.uk/postgraduate/phd/apply/applying. Please clearly state the prospective main supervisor in the respective box and select ‘School
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measurements. Desirable Interview / Application Experience of CFD of reacting flow. Desirable Interview / Application Further Information Grade 7 Salary £38,784 - £47,389 Work arrangement Full-time Duration 01
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universities. We are always looking to work with talented and motivated scientists. Funding Notes This project is for Self-funded students or students with external funding. References https://sheffield.ac.uk
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, multiscale, high-fidelity simulations that emulate in real-time the state of a corresponding physical twin based on historical and real-time sensor data. The comparison of physical and virtual data throughout