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classification accuracy assessment. ii) Involved in supporting an electrophysiology-based machine learning model to predict dormancy break. You will be part of a multidisciplinary academic and industry team
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of degradation pathways and shelf-life prediction. The aim of project is the safe integration of machine learning methods within the biopharmaceutical development process. This project offers an opportunity to be
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machine learning, coupled fire behavior/fire atmosphere modeling, air quality modeling, and system evaluation. Depending on their skills and interests, they can participate in various aspects of the project
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in writing grant applications and working with machine learning approaches such as MaxEnt, random forest, neural network. Experience using Geographical Information Systems and ecological niche modeling
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. Qualifications The ideal candidate should have a strong background in the mathematical and computational aspects of modeling subsurface and surface flows. Knowledge in machine learning, data assimilation, and
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algorithm development, modeling machine learning, and scientific simulation ▪ Ability to work well in an interdisciplinary environment, and to collaborate with experimentalists ▪ Strong oral and written
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transcriptomic data, that will be integrated with clinical metadata and whole-genome data for developing machine learning models to identify and predict patient factors driving toxicity response and sensitivity
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, Software Engineering, or a related field. Demonstrated experience in deep learning and large language model research, joint modality representation learning, knowledge graph construction, particularly in
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100%, Zurich, fixed-term We are seeking a highly motivated and skilled Postdoctoral Fellow in Machine Learning for Infectious Disease Diagnostics to join our dynamic and interdisciplinary research
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development of future proposals for funding, into AI for renewable energy. You will consider ways in which the integration of machine learning algorithms might support the wider integration of, and uptake