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of language, seeks to use bespoke probabilistic models and/or computational simulations to study possible routes of the evolution of human pragmatic practices. As a starting point, the project seeks to develop
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Your Job: Modeling and characterization at molecular level of selected biological processes by performing classical molecular dynamics, and employing enhanced sampling methods and machine learning
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EU MSCA doctoral (PhD) position in Materials Engineering with focus on computational optimization of
produced by PBF-LB. After identification of the most relevant parameters adopting a design of experiments strategy, a probabilistic (e.g. Gaussian Process Regression) model to describe the relationship
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. Correlating experimental, ab initio and multi-scale simulation as well as machine learning techniques is central to our mission: Development and application of advanced simulation techniques to explore and
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-driven simulations, optical remote sensing and biogeochemical modeling to predict seagrass distribution under various climate and nutrient scenarios. SEAGUARD aims to provide science-based recommendations
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research and scientific exchange. To that end, we closely interact with experimental laboratories. You will: Develop, simulate, and analyze biophysical models of infection spreading and the inflammatory
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Your Job: Research: employ on quantum field theory in curved spacetime to model photon kinematics Output: publish in peer reviewed journals, seek patent applications when possible Dissemination
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Computational Biophysics/Chemistry (see also https://constructor.university/comp_phys ). The PhD position is focused on efficient algorithms for the simulation of non-adiabatic exciton transfer dynamics in light
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Collaborative Doctoral Project (PhD Position) - AI-guided design of scaffold-free DNA nanostructures
DNA thermodynamic database, coarse-grained simulations of DNA motifs, and existing experimental data to establish an AI model that is able to guide the construction of desired secondary structures
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synthesis over all relevant length scales (e.g. cutting-edge ab initio methods, atomistic simulation methods, multi-scale modelling, machine learning) • High resolution analysis, monitoring of chemistry