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Field
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atmosphere models Strong background in mathematics, physics, engineering or related field Experience in scientific computing, including C/C++, fortran, python, or MATLAB Version control and package management
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, dynamics, robot modelling and control engineering Experience in mobile manipulators and industrial robots Programming languages/libraries: MATLAB, C++, Python, OpenCV Competent in mechanical design Entry
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gdsfactory Knowledgeable in MATLAB and Python is necessary Knowledgeable in Ansys Lumerical FDTD, MODE, INTERCONNECT, CML COMPILER, MULTIPHYSICS Prior experience in the above will be a bonus We regret to
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language, with a strong preference for Python. Desirable criteria: Additional experience in machine learning, statistical learning theory or related fields Fluency in relevant models, techniques or methods
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of machine learning techniques Proficiency using data science tools (e.g., Python, R, MATLAB, MySQL, Jupyter Notebooks) Excellent verbal and written communication skills including the ability to communicate
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learning and advanced statistical modeling * Proficient programming skills in Python and/or R, experience with machine learning and omics analysis libraries (e.g., scikit-learn, TensorFlow/PyTorch
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/biostatistics (or quantitative discipline) Knowledge and experience of various statistical packages such as R, Stata, Python Ability to adapt statistical methodology to specific research studies Demonstrates
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the appropriate area. Familiarity with statistical analysis software (e.g., STATA, R, SPSS) or computer programming (e.g. C++, Python, R) and experience working with health-related data will be advantageous
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(CFD) methods. The role focuses on transitioning legacy CFD solvers to modern, Python-based AI frameworks (e.g., PyTorch, JAX), targeting high-efficiency, scalable simulations of water-air systems with
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on machine learning Experience in time-series data analysis Proficient in coding languages, such as C, C++, Fortran, and Python Strong publication record Entry level candidates are welcome to apply The College