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Field
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. The candidate must have solid expertise in modelling biomolecular systems, with an excellent command of the GROMACS and AMBER codes. Extensive experience with hybrid classical/quantum (QM/MM) methods, as
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contribute to a major research project to improve our understanding of macroplastic pollution in coastal seas. Working at the intersection of numerical modelling and observations, you will develop simulations
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circular Netherlands by co-creating and designing an agent-based model of the Metropolitan Region of Amsterdam (MRA). The world is facing many ecological and political challenges, many of them rooted in
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engineeringEducation LevelPhD or equivalent Skills/Qualifications We are seeking a scientist with: Expertise in image-based biological tissue modeling and simulation Good command of deep learning Expertise in coding and
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controllability • Learning and calibration strategies for uncertainty-aware language model prediction • Knowledge-augmented and neuro-symbolic approaches for language-based reasoning • Evaluation and design of LLM
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of Dr. Marios Kogias as part of his ERC Starting project titled CloudNG (https://cordis.europa.eu/project/id/101220079 ). The post will be based in the Department of Computing at Imperial College London
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Inria, the French national research institute for the digital sciences | Villeneuve la Garenne, le de France | France | 28 days ago
cumbersome and costly, process-based (mechanistic) modeling has emerged as an effective alternative. However, many standard Process-Based crop Models (PBM) including STICS or DSSAT were initially built
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developing LLM-based applications using Python APIs. Experience with large scale molecular dynamics (MD) packages e.g. lammps Experience with version control (e.g., Git) and collaborative software development
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dysfunction. Building on more than two decades of development stochastic models that explain the population behaviour of immune cells subject to controlled stimulation, you will collaborate in research
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learning and/or statistics, Linux Desired skills: strong track record of papers on whole brain modeling, experience working with EEG (and/or MEG), fMRI, MRI + DTI (including tractography), simulation-based