78 parallel-computing-numerical-methods "Institute of Computer Science" PhD positions in Denmark
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-driven methods for autonomous underwater vehicles (AUV’s). The work builds on a strong foundation in time-series modelling, stochastic processes, statistical learning, and uncertainty quantification, with
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patterns representing health incidents and the development of privacy-preserving methods for visualizing health data. What you will gain: Strong expertise in statistical and computational methods for privacy
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research question is open and may relate to any of the department’s core research areas or related areas (see below). It must do so using computational methods and/or AI – possibly in combination with more
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pumping technologies for future electrified energy systems. We are currently recruiting a PhD candidate at DTU for a project on the multi-physics modelling of bearingless pumps. A parallel PhD position is
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funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description The Graduate School at Arts
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7 Aug 2026 Job Information Organisation/Company Technical University Of Denmark Department DTU Compute Research Field Computer science Engineering Researcher Profile First Stage Researcher (R1
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related to multiparty computation in quantum networks. The stipend is open for appointment from 1st November 2026 or soon hereafter. The duration of the position is three years. Your work tasks The
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candidate therefore has a high academic level and a good grasp of research designs and methods. Strong computational skills are necessary. The application deadline is 15 September 2026, at 11.59 PM/23.59
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Role Description This is a full-time (37 hours/week) on-site role located at Åbogade 34, 8200 Aarhus N, Denmark for a Postdoctoral Fellow at the Department of Computer Science, Aarhus University
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numerical modelling, simulation, optimization, control, or engineering-data analysis. Good programming skills in Python, MATLAB/Simulink, or a comparable scientific computing environment. A fundamental