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from animal studies to humans) in drug discovery, dynamical systems for long-horizon time series forecasting, and verifiably safe reinforcement learning. While both PhD positions are part of the same
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for a full-time, on-site PhD position in machine learning, forecasting and time series analysis. Reykjavik University, Department of Engineering. Duration: 3 years. Start date: Negotiable. Reykjavik
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the Portuguese Labour Code approved by the Law no. 7/2009 of February 12th, as amended. The contract should have a forecasted duration of 12 months and should not be extended further than the project duration and
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potential of classical and innovative fertility forecasting methods in the context of the Czech Republic Profile of the graduate In addition to the scientific and pedagogical pathway at universities, a
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safety. In particular, the candidate will investigate and further develop statistical and machine learning methods for modelling and forecasting traffic safety outcomes, and contribute to data collection
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Job Description Do you want to shape the digital backbone of the green energy transition by enabling grid operators, forecast providers, and aggregators to privately and securely share data and
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experience in the processing and integration of massive datasets (‘big data’), they will contribute to ecological modelling, environmental impact forecasting, and soil biodiversity analysis in the central
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Description The overarching mission is to conduct research combining machine learning, data assimilation, and physical modeling to enhance short-term (days/weeks) forecasts of Arctic sea ice conditions. The
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conceptualized as a specialized form of anomaly detection. Specifically, the objective is to identify anomalies that evolve gradually and to forecast the time-to-failure with sufficient accuracy. Consequently
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systems such as flashback which can occur with hydrogen or blow-off with ammonia. Currently, we cannot accurately forecast such extreme events due to the chaotic nature of the underlying turbulent flows and