179 coding-"https:"-"Prof"-"FEMTO-ST" "https:" "https:" "https:" "https:" "https:" "Tampere University" PhD positions in United Kingdom
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and deploy advanced deep learning and foundation models for surgical scene understanding segmentation, tracking, and operator assistance. You will write, test, and optimise Python and C++ code for real
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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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discipline *Candidates who have not yet been officially awarded their PhD will be appointed as Research Assistant. Expertise in atmospheric physics and chemistry Enthusiasm for coding of complex atmospheric
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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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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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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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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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and Experience Strong statistical analysis and data handling skills Understanding of data structures, data modelling and data management Ability to write robust, reproducible code in Python or R
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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