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Field
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systems. Proven programming skills in Python, R, or a comparable language. Interest in developing methodologies to assess localized climate hazards, exposure, and vulnerability as inputs to impact-based
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, machine learning, and programming (preferably Python) is highly valued. Effective communication with clinicians and interdisciplinary researchers is crucial, and excellent proficiency in English is required
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Language Processing, Artificial Intelligence, Computational Linguistics or a related field; Strong background in NLP, machine learning, and deep learning. Excellent programming skills (preferably in Python), with
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or a related field. You possess solid knowledge of core web technologies. You have solid experience in Python and JavaScript programming languages. You preferably have experience with building and using
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programming skills (preferably in Python), with experience in fine-tuning language models and working with deep learning frameworks (e.g., PyTorch); Interest in interdisciplinary research (e.g., HCI
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(or strong willingness to learn) in programming and data analysis (e.g. Python, MATLAB, R, Fortran, or similar). Curiosity and motivation to work on fire emissions, air quality, and climate questions. Ability
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explainable AI. (This point is about your motivation, not about the courses you have taken.) Programming skills: You should have very good programming skills in Python or similar, which allow you to effectively
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You have a strong affinity for both experimental science and advanced data analysis using Matlab and/or Python. You have a deep understanding of muscle exercise physiology/or human physiology, from
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explainable AI. (This point is about your motivation, not about the courses you have taken.) Programming skills: You should have very good programming skills in Python or similar, which allow you to effectively
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to acquire missing skills during the project in your motivation letter. Skills that are considered a plus: Programming for data analysis (e.g., R, Python) Multivariate data analysis, chemometrics and/or