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, interactomics, structural biology, and imaging datasets into predictive computational frameworks. Application of atomistic simulations, coarse-grained modeling, RNA folding prediction, RNA-protein and RNA-small
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of artificial intelligence, atomistic simulation, and materials science, starting in September 2026 or by mutual agreement. Our group develops computational methods to accelerate the discovery and design of
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2 PhD Positions in Computational Modelling of Biological Membranes and Adaptive Functional Materials
, you will perform atomistic and coarse-grained molecular dynamics simulations to investigate asymmetric plasma membranes, protein–lipid interactions, membrane domain formation, and the role of sterols
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to predict materials properties is essential to improve materials design methods. This research will focus on the development and integration of first principle calculations; atomistic simulations; and/or
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, or foundation models. Familiarity with atomistic simulations (e.g., density functional theory, molecular dynamics). Interest in developing broadly applicable machine-learning methods for physical sciences
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Overview Molecular spins combine the coherence, optical readout, and room-temperature operation of solid-state spin qubits with the atomistic tunability and nanoscale modularity of synthetic
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principles simulations of semiconductor and insulators Experience in developing and using codes for large scale atomistic simulations Strong demonstration of communication skills through peer-reviewed journal
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Two DTU Tenure Track Assistant Professors in Autonomous Modelling and in Robotic Synthesis of Ene...
and robotics. As the successful candidate, you will develop innovative research programs spanning atomistic and mesoscopic materials simulations, machine learning, foundation and surrogate models
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or other stochastic simulation methods Numerical solution of coupled differential or rate equations Atomistic or mesoscale modeling of materials Semiconductor nanocrystals, surfaces, or colloidal growth
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(electrolytes) full cells will be validated. Interfacial structure–function relationships will be further assessed using atomistic input from DC7. Expected results (1) Practical methodologies to prevent