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Field
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experiment on a metric-scale concrete wall, using the multi-physics NDE probe integrated onto drone platforms. Expected Results A Python-based multi-physics Maching Learning framework for NDE characterization
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development experience, and simulation/prototype development experience in MATLAB, Python, and/or OCTAVE and experiences in system level simulation and testing. Focus on problem solving and self-motivated
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(CAD) software (e.g., SolidWorks, AutoCAD) Basic programming skills (e.g., Python) Experience with system automation tools / microcontrollers (e.g., Arduino, LabJack) Experience with scientific writing
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Engineering, Physics or similar is required Knowledge of at least one programming language is expected: Python, Matlab, Fortran, C++, … Experience and/or keen interest in transport modeling of porous systems
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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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the simulation models using appropriate tools (e.g., AnyLogic, Simio, Siemens Plant Sim, Python, MATLAB or other relevant simulation platforms) Evaluate and validate the proposed framework and assess its impact on
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field Has strong interest in methodological research in healthcare Has experience with NLP and/or language modeling techniques Has solid programming skills (e.g., Python) Is motivated to work at the
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techniques e.g. laser and optical instrumentation; computational/numerical modelling programming skills e.g. Python, C++. Eligibility Open to both UK and International applicants, including EU applicants. How
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Programming experience in Python Excellent communication skills and fluency in English Collaborative personality with attention for detail Bonus but not required Experience in imaging or spatial omics data
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familiar with data analysis using programming languages like R, and/or Python. You have excellent communication skills and a willingness to collaborate across disciplines. You fit to us: if you have strong