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including in programming languages such as R and Python. Excellent publication record in peer-reviewed journals or conferences Experience of working in multidisciplinary projects including interaction with
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imagingGood organisational skills and attention to detail Experience in data analytics, statistical analysis and in programming (such as MatLab, R, Python) Ability to write papers for high quality peer-reviewed
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skills and attributes for success: A PhD (or equivalent) in a relevant subject (Artificial Intelligence, or Data Science), with training or skills relevant to the project (Python-based data collection and
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or equivalent experience in an appropriate discipline A background in numerical ice-sheet, glacier or fracture modelling, or equivalent experience Robust experience with computer coding (e.g., Python, C++) Track
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, computational biology, computer science, data science or a related subject area and proven knowledge of python programming, developing machine learning/AI based tools and HPC. You will be expected to work as part
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at . About you You must have a PhD in bioinformatics, biosciences, computational biology, computer science, data science or a related subject area and proven knowledge of python programming, developing machine
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methods to economic and environmental problems; Knowledge of STATA, R, Python and/or other relevant programming skills for undertaking applied analysis (e.g. machine learning) and handling large
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(e.g., C/C++, Python or MATLAB). • Excellent verbal and written communication skills • Excellent teamwork skills, with the ability to collaborate effectively across disciplines. This milestone
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communication journals Demonstrable proficiency in advanced quantitative data analysis: applied machine learning, statistical analysis, and handling complex data. Programming skills in Python and R are essential
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-intensive field Proficiency in Python (or R), version control, and clean code practices Experience with omics data analysis and integration Hands-on expertise in developing and fitting executable models