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Application deadline: All year round Research theme: Environmental geochemistry How to apply: https://uom.link/pgr-apply-2425 This 3.5-year PhD studentship is open to EU, UK, and US applicants. The
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modelling, ideally with the use of innovative computational methods (e.g. agent-based and predictive modelling, bioinformatics). Relevance of research to human evolution is required. The position has a
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systems; Improves prediction accuracy and computational efficiency through fine-resolution data fusion, bias correction, and model surrogate development; and Conducts experiments comparing AI-enhanced
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plants with material co-production in energy system optimization models including, e.g., reservoir productivity predictions, novel surface processes for CRM extraction, CO₂ reinjection, and reconversion
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mining challenges. The overarching objective of this project is to develop computational models that can predict how effectively glycine-based solutions extract precious metals from ore, enabling
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Modeling Center (EMC) and Climate Prediction Center scientists in the design of numerical experiments. Required Qualifications: Terminal degree in a related field or the equivalent combination of education
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to work effectively in an interdisciplinary team. PREFERRED QUALIFICATIONS Experience with one or more of the following: knowledge graphs, graph machine learning, link prediction, representation learning
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, artificial intelligence and robotics, data science, cognitive and brain science and economics and finance. Leveraging its ‘4-in-1’ model of education and residential college system, UM provides all-round
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to capture the spatial complexity of tumor organization and its relationship to treatment response. This PhD project aims to develop robust multimodal predictive models of platinum resistance using a large
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incorporate clinical, lifestyle, and nutritional factors to build predictive models through advanced bioinformatics and machine learning. By identifying molecular signatures that distinguish responders from non