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simulations using DFT (particularly of surface processes); kinetic Monte Carlo simulations; molecular dynamics simulations; classical and machine-learned force fields. Highly developed skills in scientific
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invites applicants for four PhD Fellowships in subsurface characterization within geosciences, reservoir engineering, molecular modelling, and machine learning at the Faculty of Science and Technology
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their final master exam before 15.07.2025. It is a condition of employment that the master's degree has been awarded. Experience from molecular dynamics (MD) simulations is a requirement. Experience with the
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: Quantum simulation with Rydberg atom arrays (theory) Research Area: Atomic, molecular, and optical physics (AMO), quantum control, quantum simulation Relevant Fields: Quantum information science, quantum
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models with a key focus on integrating pathology, radiology, and electronic health records (EHRs), while collaborating with the bioinformatics team to incorporate molecular data such as bulk RNA-Seq, whole
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models with a key focus on integrating pathology, radiology, and electronic health records (EHRs), while collaborating with the bioinformatics team to incorporate molecular data such as bulk RNA-Seq, whole
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: Quantum Simulation with Rydberg Atom Arrays (Experiment) Research Area: Atomic, molecular, and optical physics (AMO), quantum control, quantum simulation Relevant Fields: Quantum information science
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oral communication skills. Proficiency in experimental techniques such as microscopy, microfluidics, or rheology OR molecular dynamics simulation or agent-based simulation. Competent in soft skills e.g
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processes as droplets/condensates wet membrane compartments in cells. Numerical simulations and theoretical membrane models will be developed, aiming to couple viscous interfacial fluid flow, elastic