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Field
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) data Genetic epidemiology and Mendelian randomisation studies (with support from senior scientists) Undertake meta-analyses. Conduct meta-analyses in R or Python across a range of cardiometabolic topics
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) proficiency in programming, including Python and Matlab, data analysis, and standard Microsoft Office Suite; (c) a publication record, preferably in logistics or operational research fields; and (d
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, classification, summarization, and belief or sentiment measurement. Collecting, cleaning, merging, and managing large-scale structured and unstructured datasets using Python, R, Stata, and related tools. Assisting
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efficiency). - Contributing to scientific validation, writing publications, and disseminating results. - Software development (C++/Python) in a ROS 2 environment and robotics simulators. - Integration
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problem-solving skills and working knowledge or ability to learn languages commonly used in engineering (MATLAB, python). PREFERRED: Experience teaching subjects relevant to the curriculum. This is a one
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peer-reviewed publications Primary Platforms May Include ArcGIS Pro CityEngine Python-based geospatial processing ecosystems Cesium and 3D Tiles streaming architectures Generative AI Integration
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analysis using Matlab, Python, etc. • Some experience using software to automate experimental controls. Required Documents: (1) Curriculum Vitae (including completed degrees, list of publications, research
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reputable international venues). Experience in program analysis, intelligent software systems, or LLM-based code intelligence. Strong programming skills in Python and/or C/C++. Ability to work independently
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-QAP) statistical modeling. Responsibilities Clean, structure, and manage relational network datasets Implement and validate MR-QAP analyses using Python Conduct additional SNA metrics (e.g., centrality
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lead to a PhD position at SPMS in NTU Singapore (based on performance). Key Responsibilities: Contribute to the development of algorithms Develop codebase in Python and perform large-scale simulations