187 coding-"https:"-"Prof"-"FEMTO-ST" "https:" "https:" "https:" "https:" "https:" "https:" "PhD Jobs" PhD positions in United Kingdom
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aerodynamic understanding. Why This PhD? Work on a problem with clear industrial relevance and near-term impact Combine physics-based CFD with modern data-driven modelling Develop skills directly applicable to
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‘Course Search’ to identify your programme of study: · Search for the ‘Course Title’ using the programme code: 8100F · Research Area: Chemistry · Select ‘PhD in Chemistry (full time) as
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: Comprehensive personalised Assessment, early Risk Evaluation and clinical management” (HER-CARE) project. The successful applicant will work on the project “Assessing the role of rare germline non-coding genetic
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having good visibility of how the system and its parts respond to faults, events and trips (unlike the recent Iberian experience). For example, Statkraft is the proposer of Grid Code Modification GC0181
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experimental fluid dynamics. Experience with laboratory instrumentation, data acquisition, and coding for experiment control or data analysis (e.g. LabVIEW, MATLAB, or Python) would be beneficial. Applicants
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IrO2. We are looking for a highly motivated independent learner with good coding skills to work with us at the interface of AI and electrochemistry. As a PhD researcher, you’ll work at the forefront
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, econometrics or another relevant field. You will have substantial relevant research experience in complex trait genetics, a proven ability to code and a strong publication record. If no suitable applicant is
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of the candidate Essential requirements: A 1st class or 2.1 degree (or equivalent) in Environmental Science, Remote Sensing, Computer Science, Surveying Engineering, or related field Strong coding skills (Python
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experience with coding, e.g. MATLAB or LabVIEW, would be beneficial. Familiarity with multiphysics simulation tools is desirable. Evidence of creative thinking and the ability to work independently. Industry
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strategies and levels of fidelity. By the end of the project, the student will demonstrate the integration of ML-based boundary layer models within an open-source finite volume CFD code and quantify