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have expertise and experience in executing density functional theory (DFT) calculations, microkinetic modeling, kinetic Monte Carlo simulations, and Machine learning methods. Minimum Qualifications: Must
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sustainability, performance, and reliability. Our research leverages optimization techniques, applied machine learning, and statistical analysis to achieve these objectives. Through the DecAI project we will work
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international and most innovative employers in the region. With more than 6000 employees from 100 different countries, we are helping to build tomorrow's world every day. Through top scientific research, we push
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applications* in close collaboration with other discipline experts (software, microelectronics and applications engineers). * except for RF payloads. ** including artificial intelligence and machine learning
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data, MRI data, and other types of data. Contribute to projects at LCBC with data analysis, development, and implementation of advanced machine learning models. Write and publish scientific articles
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or a related discipline A solid background in climate and atmospheric sciences, and extreme weather ideally supported by knowledge of machine learning and time series analysis is of advantage, as is
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or Python Machine learning methods (for the baseline prediction for the reward funds) is beneficial We expect: Strong motivation to contribute to policy-relevant research Strong interest in teamwork and
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need you to have a high aptitude and passion for learning how to use new technology, and working productively with others who may have different skillsets and knowledge. You will need to be comfortable
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neuro-adaptability with changes in cortical manifestations during an intervention (e.g., non-invasive brain stimulation) for symptom reduction. Large-scale data analysis (e.g. machine-learning) will
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-fuels. To meet the growing demand of the human population we need to greatly increase the amount and different types of oil produced by crop plants. The Bates lab seeks a highly motivated postdoctoral