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focuses on utilizing Python, SQL, Azure Machine Learning, Power BI, and Power Apps to extract, analyze, and visualize healthcare data, with a primary emphasis on advancing cancer research. We invite
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to theory (20%) A review of relevant literature and theory on ice sheet resonances will be performed. Relevant theory will be coded in MATLAB (preferred) or Python (acceptable). Comparisons between theory
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benchmarking tools About you: You have prior knowledge of programming in python and are familiar with machine learning (ML) libraries in python. You have a strong interest in machine learning (ML) and deep
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programming skills (Matlab, C++ or Python) Proficiency in English for research work We regret to inform that only shortlisted candidates will be notified. Hiring Institution: NTU
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physics, and quantum error mitigation. Good programming skills in Python. Familiarity with PyTorch or tensorflow will be a bonus. Proficiency of programming skill with quantum machine learning architectures
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candidate should possess a knowledge of both time-series and frequency-domain analysis, as well as proficiency in Python or Matlab. Responsibilities include detecting cells and cellular organelles in image
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that provides a sufficient degree of background in computer science, artificial intelligence, mathematics and/or data science. Fluency in English and Python are required. Experience working with real-world
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experience building and managing clinical research databases or integrating clinical metadata into research pipelines. Strong skills in statistical analysis, data modelling, and scripting using R and/or Python
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science Python packages including numpy, pandas, and scikit-learn. Proficiency using relevant tools (Python, R, MATLAB, SQL Server, MySQL) Willingness to learn and quickly adjust to new tools and systems
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familiarity with Python, social network analysis using tools such as R), and be able to connect with social science questions and methods. The ideal candidate will conduct research at the intersection