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flexibility orchestration Scalable data and machine learning pipelines Digital twin architectures for cyber-physical energy systems AI-based energy system modeling, simulation, and optimization Secure and
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generation of scientists by offering high-quality educational programs to masters, PhD students and postdoctoral researchers (full details on http://www.iciq.org/ ). This objective is achieved by
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Your Job: This research primarily seeks to incorporate advanced neuron models, such as those capturing dendritic computation and probabilistic Bayesian network behavior, into unconventional
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-learning–based segmentation, classification and tracking for microbes and microgels in phase-contrast and fluorescence images Optimise these models and pipelines for real-time performance and integrate them
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the analysis of the state-of-the-art of the main system modeling techniques using Artificial Intelligence (AI). Drafting of relevant documents to support the preparation of the periodic reports required
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Development and application of new methods for studying allosteric regulation in chaperone complexes
methods and models for the study and simulation of protein folding processes; in the development and application of coarse-grained models for the study of the dynamics of single proteins and complexes; in
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Helmholtz-Zentrum Dresden-Rossendorf - HZDR - Helmholtz Association | Gorlitz, Sachsen | Germany | 18 days ago
tasks # Performing quantum mechanical and ML-based simulations to determine CO2 adsorption energies # Application of self-consistent continuum solvation models to account for solvation effects
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within SCI and across other departments within Pitt, and initiatives like the $11.6M Western Pennsylvania Quantum Information Core (https://www.pitt.edu/pittwire/features-articles/pitt-investment-pa
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, and verification of the monitoring network • Conducting a calibration period (approx. 3 months) to adjust detection parameters and reduce false positives/negatives. • Systematic comparison between
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equations. Your main research assignments will be to develop new models and methods for generative sampling and Bayesian inference. You will be jointly supervised by Assistant Prof. Zheng Zhao (https