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skills in R programming - Working knowledge of Python - Experience with basic analyses to characterize gut microbiomes, including diversity analysis, differential abundance analysis, modeling microbial and
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experience in battery research and proficiency in Python programming is an advantage, but not a requirement. Our offer You will join a dynamic young international research group working in state-of-the-art
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); Experience of statistical or other programming languages to manipulate large-scale datasets – e.g. Python, R; Strong quantitative skills and analytical reasoning applied to observational data; A track record
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Randomization, co-localisation); Experience of statistical or other programming languages to manipulate large-scale datasets – e.g. Python, R; Strong quantitative skills and analytical reasoning applied
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simulators. Proficiency in Python, including data handling (pandas, NumPy), visualization (matplotlib) and integration within simulation workflows. Understanding of sector coupling (e.g. P2G, P2H), energy
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, and Abilities Proficiency in programming languages commonly used in data analysis and machine learning, such as Python, R, or MATLAB. Must have effective oral and written communication skills; and
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mathematics, computer science, physics, biomedical or electrical engineering or similar disciplines. Good programming expertise (Matlab, C++, Python or equivalent) and experience with the Linux operating system
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well as strong computing skills, including the knowledge of UNIX/Linux, Fortran, Python, or other high-level languages. The post is full time and fixed term for 3 years. The closing date for applications is noon
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; proven competence in programming methods like Python; evidence of working well as part of a multidisciplinary research team. Informal enquiries may be addressed to Professor Tingting Zhu (email
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data, as in Mendelian randomization and TWAS. In addition to new methods development and evaluations, the job responsibilities include software development (mostly in R, or in Python/TensorFlow/Keras