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informed neural networks (PINN) and explainable machine learning (EML) frameworks; experience in related technologies including large-scale data analysis, deep learning, Python, PyTorch; and the ability
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-based sensor data to enhance the prediction of peatland soil properties and functions. You will focus on leveraging machine learning/deep learning techniques along with explainable artificial intelligence
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-based sensor data to enhance the prediction of peatland soil properties and functions. You will focus on leveraging machine learning/deep learning techniques along with explainable artificial intelligence
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expertise in data science, with hands-on experience in techniques such as machine learning, reinforcement learning, and simulations, and in handling large-scale, within-person, or real-time datasets; A strong
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postdoctoral associate positions, starting immediately. Dr. Liu has extensive experience in big data analytics, systems biology, probabilistic graphical models, causal inference and machine learning. Dr. Liu's
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(UQ) for machine learning and its validation. Your areas of research will be chosen based on both your own expert judgement and insight into trends and developments and on team requirements to ensure
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, leadership, and data science. Special training for writing successful ERC Starting Grants as a ‘ticket’ to an outstanding academic career. Being part of a thriving academic and social community in Vienna, one
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variables, fixed effects for panel data, matching estimators, or machine learning) or other advanced statistical modelling.- Advanced programming skills in Stata, R, Python or a similar software.- Strong
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d) excellent written, oral communication skills e) strong data analysis skills. Ideal applicants will also have experience with some combination of: a) Machine learning e) code optimization and
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Experience with machine learning, data mining and data assimilation is a plus Knowledge of git, docker, kubernetes, and/or metadata is a plus Ability to work within a team Excellent interpersonal and