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Field
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quantitative and analytical skills. Experience with programming and data analysis (preferably in R; experience with Python, Julia, Matlab, or similar is also valuable). Experience in using AI to operate said
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release of hydrophobic drugs from lipid nanocarriers. The candidate will hold a M.Sc. in pharmacy and preferably has previous experiences with scientific programming (e.g. Matlab, R). The candidate must be
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/Electromagnetics theory, design and simulations Machinelearning mathematics and algorithms Numerical methods Programming skills (Python, MATLAB, or similar) Strong analytical and problem-solving skills. Good written
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neuroimaging data Proven record of ability to conduct high quality research in relevant health related subject Previous coding experience (e.g. python, bash, matlab) Good administrative skills, and the ability
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, monitoring, data acquisition and processing in MATLAB and cross-platform Python (Windows and Linux) and experience in integration of systems for synchronised acquisition and aggregation of data sources
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resource recovery applications. You will combine numerical modelling in tools such as MATLAB and COMSOL with experimental work in the laboratory, where you set up and operate test rigs, characterize water
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Knowledge, Skills and Behaviours Demonstrable experience in quantitative or computational modelling Strong programming skills (e.g. R, MatLab, or similar) Ability to develop and analyse mathematical
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, including time series analysis and statistics (e.g. mixed effects modelling) Capacity to develop computer code and experience with programming languages (Matlab, Python, R) and geospatial tools (e.g. ArcGIS
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/or MATLAB). Experience with C++ and maintenance of complex software implementations. Experience with CUDA is a strong plus. Ability to design, conduct, and analyse controlled experiments, both in
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, mathematics, or related scientific disciplines. Skills in numerical tools and programming are desirable (MATLAB, python, C++ etc). Any experience or capabilities in engineering design or manufacturing methods