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of neural hydrology, where hydrological models are directly learned from data via machine learning (e.g., LSTM neural networks, [1]). Initially, these models ignored all physical background knowledge and did
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feedback control, you will uncover fundamental connections between physical dynamics and neural network representations. We seek a highly motivated PhD candidate with an excellent master’s degree in physics
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Researcher (PhD Position, m/f/d) Neural Circuits and Behavior This position is limited in accordance with § 2 WissZeitVG and § 72 HessHG, offering the opportunity for individual academic qualification and with
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– from the modeling of material behavior to the development of the material to the finished component. PhD Position in Machine Learning and Computer Simulation Reference code: 50145735_2 – 2025/WD 1
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to understand, predict, and treat diseases. You will work with multimodal biomedical datasets including omics, imaging, and patient data and apply cutting-edge AI models such as graph neural networks, transformer
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: Reference number 3694: PhD student researching and developing alternative methods to animal testing (f/m/d) Pay grade: 13 TVöD Place of work: Berlin and Hannover Limited for three years Application deadline