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Field
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application of ultrafast THz-pump and optical-probe techniques to detect narrow-band THz radiation and explore mode-selective dynamics in quantum and molecular systems. This work leverages state-of-the-art
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harvest “big data” allowing agnostic and dynamic collection of information, to deliver a new class of research that will enable a better understanding of the clinical, molecular, behavioural and
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Healthcare Monitoring We welcome applications from those with expertise in or across these disciplines: Computational materials modeling: DFT, molecular dynamics, phase-field modeling, or multiscale
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: Computational materials modeling: DFT, molecular dynamics, phase-field modeling, or multiscale simulations. Data-driven materials discovery: ML models for property prediction, materials design, or synthesis
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background in computational and/or mechanistic modelling of physical, chemical, or biological systems (e.g., PBPK, molecular dynamics) Experience with cheminformatics libraries and chemical datasets is an
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comprehensive simulation open-source codes. Experience in data analysis and simulations of complex and coupled nuclear engineering problems, using techniques such as (but not limited to) molecular dynamics
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will design a novel, highly coarse-grained model of the nanocarrier and use Brownian dynamics simulations to investigate its assembly and disassembly mechanisms in relation to nutrient loading capacity
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Scarcity and Quality Dynamics: Investigate methods for addressing sparse labels, non-standard metadata, and imbalanced datasets to improve AI training robustness across scientific domains. Privacy and
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, and develops various tools for bioimage analysis, mostly using machine learning and AI-based models. As a postdoc you will conduct research using various methods in cell-and molecular biology, but
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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