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developing a digital twin, employing machine learning and numerical computations of atomistic processes. At IKZ, a kinetic Monte Carlo tool has been developed in the programming language julia. This allows a
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numerical modeling and validation of brain-inspired algorithms Develop circuit-plausible training and inference algorithms, and analyze their behavior in LTspice and Cadence Spectre Perform algorithm–circuit
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models. Expected Results: Ability to assess the influence of demise process on the release of emissions into different atmospheric layers. Numerical model to describe the temporal and spatial dispersion
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Your Job: This PhD project focuses on modelling and simulating future gas grids, exploring transformation pathways, and developing cross-sectoral simulation frameworks to support informed decision
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Heidelberg University is a comprehensive university with a strong focus on research and an international standards. With around 31,300 students and 8,400 employees, including numerous top
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benchmarking of clay mineral surface finite models for DFT simulations Speciation simulations of the radionuclides in various environments Your profile Completed university studies (Master/Diploma) in the field
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management scenarios using geophysics and numerical modeling. High-resolution subsoil characterization using electromagnetic induction (EMI), and ground penetrating radar (GPR) will be combined with soil
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quantitative image analysis, numerical modeling, and explainable AI (XAI) with state-of-the-art biophysical methods. Using techniques such as traction force microscopy, microfluidics, 3D bioprinting, and
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calcifications present in the retina. The core project of the doctoral candidate will involve testing various forms of application in animal models. We have numerous state-of-the-art technologies at our disposal
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design recovery and stability strategies using large-scale simulation workflows. Build and expand realistic, continent-scale power system models (e.g., the European transmission grid). Implement and test