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Field
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Principal Investigator of the OrDOTime project, and a collaborator on the project. Literature review, design of behavioural experiments, data collection, data analysis, writing scientific articles
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-Chem simulations for modeling aerosols and clouds in the Arctic region. - Analysis of the interactions between aerosols, clouds, and climate using data from the simulations. - Validation of the models
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for students, line-manage Research Assistants and D.Phil. students, mentor on methods, analysis and career development About You You will hold a Ph.D/D.Phil in a quantitative or theoretical discipline (e.g
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to scientific computing and other scientific domains. Candidates with strong backgrounds in stochastic analysis, numerical analysis, sampling methods, optimization, scientific computing, or related areas
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Austrian Academy of Sciences, The Institute for Habsburg and Balkan Studies (IHB) | Austria | 15 days ago
guidelines, co-supervising two student assistants Conduct in-depth historical and philological analysis of the Frangochiotika sources jointly with the PI Lead the project's micro-level analysis of vernacular
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should have: strong expertise in cosmology, general relativity, modified gravity, gravitational physics or relativistic astrophysics; experience with analytical and/or numerical research methods relevant
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PostDoc in aerobiological modelling Are you interested in atmospheric science and can you contribute to the development of a new generation of numerical models describing concentrations and
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material and extracts. He or she will also contribute to the processing, annotation and analysis of the metabolomic data obtained.The project will thus establish a reference resource for the study of plant
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National Aeronautics and Space Administration (NASA) | Greenbelt, Maryland | United States | about 10 hours ago
programming (Python, MATLAB, IDL) with experience in data analysis, visualization, optical raytracing, and simulation software. Ability to develop custom analysis tools. Knowledge of numerical methods
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: atmospheric convection, radiative transfer, climate change, atmospheric/fluid dynamics, or machine learning. Proficiency in numerical analysis and high-performance computing. Experience with atmosphere/climate