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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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data, spatial modelling, multivariate statistics and/or machine learning, and relevant coding languages (e.g. R, Python), including a sound understanding of FAIR data principles, data management and
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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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working with refugee and asylum seeker populations. Strong skills in statistical analysis, manuscript preparation and the use of software such as SPSS, Stata, R or Python are also essential. This is a rare
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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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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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classification. Strong background in experimental design, statistical sampling and analysis in field settings. Skilled in GNSS‑based geolocation, GIS software (e.g. QGIS, ArcGIS) and programming (Python, R
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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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. Desirable: Proficiency in scientific programming (e.g. Python) and familiarity with data science and machine learning techniques. Experience with geochemical analytical techniques and working in a laboratory