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Applying and developing Machine Learning methods for the prediction of thermodynamic properties (Enthalpies of formation, amorphization temperatures, etc.) of compound materials such as solid solutions of Lanthanides orthophosphates.<br>
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Methods: Regression using KRR (Gaussian, Laplacian, polynomial) and knowledge extraction through feature sparsification using LASSO + $`\ell_0`$.
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* **[Modeling & Simulation Group](https://fz-juelich.de/ibg/ibg-1/modsim)** (at IBG-1)<br>
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* **[Modeling & Simulation Group](https://fz-juelich.de/ibg/ibg-1/modsim)** at IBG-1<br>
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Contact: [Christian Sachs](https://fz-juelich.de/SharedDocs/Personen/IBG/IBG-1/EN/Research_groups/microscale/sachs.html?nn=982498), [c.sachs@fz-juelich.de](mailto:c.sachs@fz-juelich.de); [Katharina Nöh](https://fz-juelich.de/SharedDocs/Personen/IBG/IBG-1/EN/Research_groups/modsim/noeh.html?nn=982498), [k.noeh@fz-juelich.de](mailto:k.noeh@fz-juelich.de)<br>
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Data: Image data (microscope time-lapse stacks of microfluidic experiments; bacteria, algae, yeast)<br>
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Methods: convolutional neural network (CNN) based pixel-precise multi-instance segmentation (via U-Nets)<br>
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