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years and in the relevant areas of Machine Learning / Artificial Intelligence, Credit Risk Modeling and Operations Optimization Modeling; The candidate must have strong programming skills in Python, and
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systems. Proficiency with commercial modelling software, e.g., ANYSYS Fluent, or open-source modelling platforms such as OpenFOAM or Python. How to apply Candidates should apply online, carefully answer all
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programming languages (e.g., Python, R, Matlab). Demonstrate excellent communication skills for articulating research in presentations and publications. Show a track record of publishing in peer-reviewed
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), chemistry, statistics, biochemistry or a related discipline Have expertise in programming and quantitative data analysis, including machine learning in a software such as R/Python Have a developing ability to
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PhD registration at Imperial College London. Experience in energy systems modelling, techno-economic analysis, or renewable energy integration Familiarity with modelling tools such as Python, MATLAB
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; or Experience with high-fidelity solvers, e.g. SU2, OpenFoam, StarCCM+, Fluent; Proficiency in programming, e.g. Python, Matlab, C; Experience utilizing high-performance computing (HPC) to parallelize workflows
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track-record conducting research using large-scale routine or registry data, preferably in cancer High-level proficiency and experience in R, Stata, or Python, with demonstrable experience applying open
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or Python. How to apply Candidates should apply online, carefully answer all the application form questions, and attach a curriculum vitae (with details on education, research experiences, successes and the
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. Experience in developing xApps and rApps is an advantage. Proficiency in Linux system administration, virtualization (Docker/Kubernetes), and scripting (Python, Bash). Strong programming skills in Python or C
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, conducting advanced statistical analyses in Python, R, and Stata, and leading systematic and Bayesian meta-analyses. The role also includes weekly clinics, trial support, and active contribution to academic