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) Required Experience 4 years If any experience is required, please specify what kind of experience: UNIX systems administration, as a central and daily focus, with emphasis on shell or Python scripting
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to create working prototypes. You may be comfortable working with software such as Linux, ROS, Python etc. You will be part of a diverse team who are responsible for designing, building, programming, testing
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artificial intelligence in health research. Responsibilities Assist with data preprocessing and analysis of large neuroimaging datasets Support development and evaluation of machine learning models in Python
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data analytics concepts, including data cleaning, analysis, and visualization. Guide learners in the use of industry-standard tools such as spreadsheets, SQL, Tableau, Power BI, R, or Python, as
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expertise in object-oriented programming in Python, data modeling, and scientific workflows experience in collaborative Linux-based development using Git knowledge of Python-based type systems and schemas
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with the microfluidic live-cell imaging platform and provide Python/Jupyter-based tools for collaborators, contributing to FAIR datasets and open-source software (Co-)Supervise student projects at BSc
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(supervised, unsupervised, deep learning) Develop and test Python notebooks for lab exercises Support containerization using Docker and virtualized environments Document lab procedures and contribute to public
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analyses using Stata and Python. Review relevant academic literature and summarize findings. Prepare tables, figures, and documentation for research papers and presentations. Support other research
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: Develop applications using C#/.NET Core, Node.js, Python, with React/Angular frontends. Integrate LLM APIs and build AI-powered features. AI Feature Integration: Implement LLM APIs (OpenAI, Anthropic
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, dimensionality reduction, clustering, trajectory modeling) Lead reproducible analysis pipelines in R, Python, or related frameworks Interpret results in biological and clinical context, with emphasis