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theoretical models and numerical tools (master equations, quantum trajectory simulations) to investigate coupling regimes, dynamical phase transitions, and the effects of collective dissipation on coherence and
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is close. Our cohesive campuses make it easy to meet, work together and exchange knowledge, which promotes a dynamic and open culture. The ongoing societal transformation and large green investments in
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Join us to pioneer next-generation generative models that accelerate molecular dynamics. We seek a postdoctoral researcher to develop AI surrogates for molecular dynamics (MD), slashing
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optimization code used, particularly for automated transition state searches. • Perform molecular dynamics simulations to estimate thermodynamic/macroscopic properties. IPREM brings together over 300 staff
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correction, or many-body quantum systems. o Proficiency in numerical simulations (e.g., tensor networks, quantum circuit modeling). · For Experimentalists: o PhD in atomic/molecular/optical (AMO) physics
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microbial pathogenesis. Research spans both cellular and molecular aspects of infections caused by bacteria, viruses, and fungi, as well as immune regulation of these processes. The department comprises
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with surface science. Experience with molecular dynamics simulations and at least basic knowledge of machine-learning approaches for atomistic modeling are highly desirable. Skills in Python and
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cost of MD simulations by several orders of magnitude. Notable examples of our work in this area include Boltzmann Generators [1 ,2 ], Surrogate-model Assisted Molecular Dynamics [3 ], and Implicit
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Polymers using a combination of quantum and force field-based simulations that will be further integrated into a force field-based Molecular Dynamics (MD) approaches to assess the permeability and
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, high-throughput simulations, molecular dynamics, and materials chemistry. Strong Python programming skills are required, and prior experience with developing open-source software or databases will be