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) An interest in AI/ML and multi-omics integration. Solid background in statistical genetics and computational biology; experience with R, Python, or equivalent programming languages is essential. Passion
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successful for this position, you'll have: Demonstrated experience in the application of LLM. Demonstrated experience in programming in Python. Ability to learn new technology and new tools rapidly. Good
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experience in python, C++ or other relevant language and experience in deep neural networks Strong mathematical capability, especially for Theme 1, with applicants holding an undergraduate or postgraduate
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PhD in Computer Science, Engineering or other Machine Learning-related field. • Programming experience in python, C++ or other relevant language and experience in deep neural networks • Strong
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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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materials. Evidence of publications in high-quality peer-reviewed journals and presentations at major conferences. Proficiency in data analysis and relevant tools (e.g. Python, MATLAB, WSxM, Gwyddion). Strong
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developing and implementing algorithms for processing, imaging or inversion of seismic data, preferably using MATLAB and/or Python. Experience or demonstrated ability in processing and analysis of surface
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using programming languages such as Python or R. Communication and Organisational Skills: Excellent problem-solving skills, with the ability to plan, prioritise, and manage multiple tasks efficiently
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statistical / data science languages such as R or Python Experience working with geographic information systems Desirable Characteristics: Experience with building spatially explicit models, including