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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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, Physics (computational or solid-state focus), or a related field Strong interest in additive manufacturing, topology optimization, computational design, and process modelling Background in numerical methods
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forecasting and analysis of risk metrics. Experience working with highly complex litigated claims, attorneys, third party administrators and other parties involved in the process. Experience in strong
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will play a key role in strengthening and expanding the group’s computational capabilities for the simulation, analysis, and optimization of advanced thermal energy systems and processes. This includes
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of helicity-preserving scatterers (dual or quasi-dual meta-atoms) in the microwave regime. The work will involve both theoretical and numerical aspects: understanding the conditions for duality symmetry and
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, version control) and numerical workflows. Experience programming for data analysis and model workflows (e.g., Python, MATLAB; FORTRAN/C familiarity for model configuration). Demonstrated verbal and written
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high-performance classical simulations, working at the interface between quantum theory, numerical methods, and large-scale scientific data analysis. The position is not limited to quantum computing and
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transfer This research combines advanced numerical simulation and artificial intelligence to develop predictive models for high-temperature multiphase flows, with specific relevance to steel casting
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. -Analyze budget data and prepare management reports on current status as well as forecasting and trend analysis. Make recommendations to AVC and directors on financial planning. -Develop tools to monitor
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policies/procedures that ensure compliance with Graduate Studies rules, regulations and deadlines. Independent analysis, interpretation and administration of numerous and intricate regulations, policies and