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offer visa sponsorship for this role. Candidate requirements Essential Skills in programming, preferably in Python, and a suitable undergraduate / masters degree in the discipline of Computer Science, NLP
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expertise across all three. Good mathematical and analytical skills. Programming experience (such as Python, MATLAB, or similar) for simulation-based research, or be willing to develop this during the PhD
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• Possess at least a bachelor’s degree in computer science, Information Systems, Engineering, or a related field. • Strong full-stack development skills (e.g., Node.js, React/Vue, Python
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tools such as R, Python, SPSS, Stata, or equivalent. Familiarity with Generative AI applications, prompt engineering, chatbot technologies, or learning analytics is advantageous. Strong academic writing
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systems in production environments, with deep knowledge of contemporary AI frameworks, tools, and best practices. Software Engineering: Excellent software development skills with proficiency in Python
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control components into a standalone measurement unit and establish a standardized, repeatable image-acquisition procedure. Develop Python-based image-processing and annotation workflows and train and
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scenarios. The researcher will develop profit–risk–environment tradeoff products, build reusable R/Python workflows, and publish and present results in collaboration with USDA-ARS and university partners
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with RTDS/RSCAD, real-time simulation or hardware-in-the-loop set-ups. Software development skills: Python, C, scripting and automation, version control, testing. Expertise in one or more of: converter
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) to soft matter or related systems; basic knowledge of scattering data modelling is essential. Data analysis skills and programming experience in Python or MATLAB. Ability to work effectively with multi
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skills (Python / MATLAB / LabVIEW), laboratory experience (optical/biological) and/or knowledge of advanced data analysis methods will be an added advantage, fluent English, reliability, good work