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Information Eligibility criteria * Skills/knowledge: statistical physics, physical chemistry, machine learning * Expertise: molecular simulations, programming experience (Python, C++, Julia, C, etc.), Python
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experience in remote sensing and GIS, strong programming skills (Python, R or similar), and an international publication record. Experience with machine learning and cloud computing will be considered an asset
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responsibility for our unique GPU-accelerated 3D FDTD software suite and extending its capabilities Modelling the effects of atmospheric turbulence fields Software development (3D modelling and coding in Python, C
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predictive modelling Public policy evaluation Management and analysis of survey data Software proficiency Statistical and econometric packages such as Stata, R, or Python GIS software (QGIS, ArcGIS
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and transmission dynamics using large datasets. Strong working knowledge of Python and R programming language is essential. The applicants should have a good command of spoken and written English and
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periodic time series. Responsibilities also include coding the proposed algorithms in R or Python, such as methods for splitting periodic time series into regeneration blocks, and applying them to real
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the proposed algorithms in R or Python, such as methods for splitting periodic time series into regeneration blocks, and applying them to real biomedical datasets. The role requires the ability to effectively
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: Python, Pytorch; proficiency in collaborative tools: Git Written and spoken English (B2) Ability to work interactively in a team Open-mindedness Ability to communicate Training in computer science
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. Ability to handle large volumes of data and familiarity with household surveys are required, alongside solid data analysis skills (R, Stata, Python, etc.) and familiarity with academic writing and
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include: expertise in programming and coding (preferably using Python and C++) and GUI development; expertise in computational mechanics and finite element simulation and modeling; expertise in laboratory