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environments, scripting/programming (e.g., Bash, Python, R), and genomic analysis pipelines is essential, along with hands-on experience working with large datasets and public repositories such as Genomics
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with anxiety and depression. The post-holder will need to have strong programming skills (e.g. Python, R) and will take the lead on analysing physiological data and writing up studies for publication
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large-scale microbiome or pathogen genomics datasets. They will be proficient in one or more programming languages (e.g., Python or R) and they will have knowledge of Linux/Unix, SQL, and high-performance
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PhD Expert knowledge of statistical modelling, statistical inference and use of relevant software (e.g. R/Python) both for data processing, visualisation and programming. Excellent communication and
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Strong quantitative background Experience with programming languages (e.g. MATLAB or Python) Experience with statistical software (e.g. R or Stata) Ability to work across broad scientific missions and
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of the Python scientific programming stack (e.g. pandas, numpy, jupyter, spark) and best practices for software development (e.g. version control, unit tests). Experience working with relational databases, SQL
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background in AI/NLP or speech technologies, with experience in designing and implementing machine learning models. Proficient in software development, including Python, model integration, and system
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programming languages such as C#, Python, and C++. Experience with data analysis techniques and AI methods. For informal queries please contact: Dr. Patricia Cornelio - patricia.cornelio@bristol.ac.uk To find
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large, highly diverse and multi-modal datasets (e.g., images, surveys, statistical and sensor data). Familiarity with geostatistical, GDAL, Python, PostGIS/PostgresSQL, Machine Learning, AI, Internet
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theory, market structures, game theory, and programming skills (e.g. Python, MATLAB), alongside a deep understanding of policy and market issues related to local energy communities in the UK and EU. We